CN111268011A - Self-balancing vehicle and static balance control method, device, medium and equipment thereof - Google Patents
Self-balancing vehicle and static balance control method, device, medium and equipment thereof Download PDFInfo
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- CN111268011A CN111268011A CN202010078400.XA CN202010078400A CN111268011A CN 111268011 A CN111268011 A CN 111268011A CN 202010078400 A CN202010078400 A CN 202010078400A CN 111268011 A CN111268011 A CN 111268011A
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- B—PERFORMING OPERATIONS; TRANSPORTING
- B62—LAND VEHICLES FOR TRAVELLING OTHERWISE THAN ON RAILS
- B62K—CYCLES; CYCLE FRAMES; CYCLE STEERING DEVICES; RIDER-OPERATED TERMINAL CONTROLS SPECIALLY ADAPTED FOR CYCLES; CYCLE AXLE SUSPENSIONS; CYCLE SIDE-CARS, FORECARS, OR THE LIKE
- B62K11/00—Motorcycles, engine-assisted cycles or motor scooters with one or two wheels
- B62K11/007—Automatic balancing machines with single main ground engaging wheel or coaxial wheels supporting a rider
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- B—PERFORMING OPERATIONS; TRANSPORTING
- B60—VEHICLES IN GENERAL
- B60L—PROPULSION OF ELECTRICALLY-PROPELLED VEHICLES; SUPPLYING ELECTRIC POWER FOR AUXILIARY EQUIPMENT OF ELECTRICALLY-PROPELLED VEHICLES; ELECTRODYNAMIC BRAKE SYSTEMS FOR VEHICLES IN GENERAL; MAGNETIC SUSPENSION OR LEVITATION FOR VEHICLES; MONITORING OPERATING VARIABLES OF ELECTRICALLY-PROPELLED VEHICLES; ELECTRIC SAFETY DEVICES FOR ELECTRICALLY-PROPELLED VEHICLES
- B60L15/00—Methods, circuits, or devices for controlling the traction-motor speed of electrically-propelled vehicles
- B60L15/20—Methods, circuits, or devices for controlling the traction-motor speed of electrically-propelled vehicles for control of the vehicle or its driving motor to achieve a desired performance, e.g. speed, torque, programmed variation of speed
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- G—PHYSICS
- G05—CONTROLLING; REGULATING
- G05B—CONTROL OR REGULATING SYSTEMS IN GENERAL; FUNCTIONAL ELEMENTS OF SUCH SYSTEMS; MONITORING OR TESTING ARRANGEMENTS FOR SUCH SYSTEMS OR ELEMENTS
- G05B13/00—Adaptive control systems, i.e. systems automatically adjusting themselves to have a performance which is optimum according to some preassigned criterion
- G05B13/02—Adaptive control systems, i.e. systems automatically adjusting themselves to have a performance which is optimum according to some preassigned criterion electric
- G05B13/04—Adaptive control systems, i.e. systems automatically adjusting themselves to have a performance which is optimum according to some preassigned criterion electric involving the use of models or simulators
- G05B13/042—Adaptive control systems, i.e. systems automatically adjusting themselves to have a performance which is optimum according to some preassigned criterion electric involving the use of models or simulators in which a parameter or coefficient is automatically adjusted to optimise the performance
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- G—PHYSICS
- G05—CONTROLLING; REGULATING
- G05D—SYSTEMS FOR CONTROLLING OR REGULATING NON-ELECTRIC VARIABLES
- G05D1/00—Control of position, course or altitude of land, water, air, or space vehicles, e.g. automatic pilot
- G05D1/0088—Control of position, course or altitude of land, water, air, or space vehicles, e.g. automatic pilot characterized by the autonomous decision making process, e.g. artificial intelligence, predefined behaviours
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- G—PHYSICS
- G05—CONTROLLING; REGULATING
- G05D—SYSTEMS FOR CONTROLLING OR REGULATING NON-ELECTRIC VARIABLES
- G05D1/00—Control of position, course or altitude of land, water, air, or space vehicles, e.g. automatic pilot
- G05D1/08—Control of attitude, i.e. control of roll, pitch, or yaw
- G05D1/0891—Control of attitude, i.e. control of roll, pitch, or yaw specially adapted for land vehicles
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- G—PHYSICS
- G05—CONTROLLING; REGULATING
- G05D—SYSTEMS FOR CONTROLLING OR REGULATING NON-ELECTRIC VARIABLES
- G05D17/00—Control of torque; Control of mechanical power
- G05D17/02—Control of torque; Control of mechanical power characterised by the use of electric means
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- G—PHYSICS
- G05—CONTROLLING; REGULATING
- G05D—SYSTEMS FOR CONTROLLING OR REGULATING NON-ELECTRIC VARIABLES
- G05D27/00—Simultaneous control of variables covered by two or more of main groups G05D1/00 - G05D25/00
- G05D27/02—Simultaneous control of variables covered by two or more of main groups G05D1/00 - G05D25/00 characterised by the use of electric means
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- Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
- Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
- Y02T—CLIMATE CHANGE MITIGATION TECHNOLOGIES RELATED TO TRANSPORTATION
- Y02T10/00—Road transport of goods or passengers
- Y02T10/60—Other road transportation technologies with climate change mitigation effect
- Y02T10/72—Electric energy management in electromobility
Abstract
The embodiment of the application provides a self-balancing vehicle and a static balance control method, device, medium and equipment thereof. The static balance control method comprises the following steps: acquiring a dynamic model constructed according to dynamic characteristics of a self-balancing vehicle and a physical model constructed according to physical characteristics of a momentum wheel motor; acquiring a rotation angle of a momentum wheel and an attitude angle of a self-balancing vehicle, wherein the attitude angle is an included angle between a vehicle body of the self-balancing vehicle and the gravity direction; calculating control parameters required for maintaining the self-balancing vehicle in a static balance state based on a dynamic model and a physical model, as well as the rotation angle of a momentum wheel and the attitude angle of the self-balancing vehicle; controlling the momentum wheel motor based on the control parameter. The technical scheme of the embodiment of the application can effectively realize the static balance control of the self-balancing vehicle and can ensure the stability of the control.
Description
Technical Field
The application relates to the technical field of artificial intelligence and robots, in particular to a self-balancing vehicle and a static balance control method, device, medium and equipment thereof.
Background
The balance control problem of the self-balancing vehicle is always a hot point of research, and currently, much research is carried out on the dynamic balance of the self-balancing vehicle, namely, the self-balancing vehicle is in a state of self-attitude balance realized under the conditions that the advancing speed of the self-balancing vehicle is greater than 0 and the vehicle body moves forwards along a straight line or a curve relative to the ground, while the research is lacked on the static balance of the self-balancing vehicle, which is in a state of realizing self-attitude balance in situ when the advancing speed of the self-balancing vehicle is 0.
Disclosure of Invention
The embodiment of the application provides a self-balancing vehicle and a static balance control method, a device, a medium and equipment thereof, so that the static balance control of the self-balancing vehicle can be effectively realized at least to a certain extent, and the stability of the control can be ensured.
Other features and advantages of the present application will be apparent from the following detailed description, or may be learned by practice of the application.
According to an aspect of an embodiment of the present application, there is provided a static balance control method for a self-balancing vehicle, the self-balancing vehicle including a momentum wheel and a momentum wheel motor for driving the momentum wheel to rotate, the static balance control method including: acquiring a dynamic model constructed according to the dynamic characteristics of the self-balancing vehicle and a physical model constructed according to the physical characteristics of the momentum wheel motor; acquiring a rotation angle of the momentum wheel and an attitude angle of the self-balancing vehicle, wherein the attitude angle is an included angle between a vehicle body of the self-balancing vehicle and the gravity direction; calculating control parameters required for maintaining the self-balancing vehicle in a static balance state based on the dynamic model and the physical model, as well as the rotation angle of the momentum wheel and the attitude angle of the self-balancing vehicle; controlling the momentum wheel motor based on the control parameter.
According to an aspect of an embodiment of the present application, there is provided a static balance control apparatus for a self-balancing vehicle, the self-balancing vehicle including a momentum wheel and a momentum wheel motor for driving the momentum wheel to rotate, the static balance control apparatus including: a first acquisition unit configured to acquire a dynamic model configured according to dynamic characteristics of the self-balancing vehicle, and a physical model configured according to physical characteristics of the momentum wheel motor; a second obtaining unit configured to obtain a rotation angle of the momentum wheel and an attitude angle of the self-balancing vehicle, where the attitude angle is an included angle between a vehicle body of the self-balancing vehicle and a gravity direction; a processing unit configured to calculate control parameters required to maintain the self-balancing vehicle in a static equilibrium state based on the dynamic model and the physical model, and a rotation angle of the momentum wheel and an attitude angle of the self-balancing vehicle; a control unit configured to control the momentum wheel motor based on the control parameter.
In some embodiments of the present application, based on the foregoing solution, the processing unit is configured to: fusing the dynamic model and the physical model to generate a comprehensive model for the self-balancing vehicle; determining a control matrix for controlling the momentum wheel motor according to the rotation angle of the momentum wheel, the attitude angle of the self-balancing vehicle and the comprehensive model; determining the control parameter based on the control matrix.
In some embodiments of the present application, based on the foregoing solution, the processing unit is configured to:
transferring model parameters of the physical model into the dynamic model, generating a first model containing the physical parameters of the momentum wheel motor, and taking the first model as a comprehensive model for the self-balancing vehicle; or
Transmitting the model parameters of the physical model into the dynamic model, generating a first model containing the physical parameters of the momentum wheel motor, adjusting the input parameters in the first model to the torque of the momentum wheel motor to generate a second model not containing the physical parameters of the momentum wheel motor, and taking the second model as a comprehensive model aiming at the self-balancing vehicle.
In some embodiments of the present application, based on the foregoing scheme, the corresponding equation set of the dynamical model includes:
the system of equations corresponding to the physical model comprises:
transferring model parameters of the physical model into the dynamic model, wherein the generated equation corresponding to the first model comprises:
wherein the content of the first and second substances,
；
；
representing the weight of the self-balancing vehicle except for the momentum wheel;
representing the weight of the momentum wheel;
representing the height of the center of gravity of the self-balancing vehicle;
representing the height of the momentum wheel;
representing the moment of inertia of the self-balancing vehicle except for the momentum wheel;
representing the moment of inertia of the momentum wheel;
representing the attitude angle;
representing the angle of attitude
Obtaining the attitude angular velocity by derivation;
representing the angular velocity of the attitude
Deriving the obtained attitude angular acceleration;
representing the rotation angle of the momentum wheel;
indicating the angle of rotation of the momentum wheel
Deriving the angular velocity of the momentum wheel;
representing angular velocity of the momentum wheel
Deriving the angular acceleration of the momentum wheel;
represents the acceleration of gravity;
representing the torque provided by the momentum wheel motor under the condition of neglecting the friction force;
representing a voltage of the momentum wheel motor;
and
respectively representing the inductance and the resistance of an armature coil of the momentum wheel motor;
representing the current of the momentum wheel motor;
representing a back electromagnetic force of the momentum wheel motor;
indicating the angular velocity of the momentum wheel motor,
；
representing the torque generated by the momentum wheel motor;
representing a motor torque constant;
representing a transmission ratio between the momentum wheel motor and the momentum wheel; the output parameters of the first model comprise
。
In some embodiments of the present application, based on the foregoing scheme, the input parameter in the first model is adjusted to the torque of the momentum wheel motor, and the generated equation corresponding to the second model includes:
wherein the output parameters of the second model comprise
。
In some embodiments of the present application, based on the foregoing solution, the processing unit is configured to: converting the comprehensive model into a state space expression; generating a target equation for solving a control matrix contained in a feedback control equation according to the feedback control equation and the state space expression; constructing a loss function based on the input parameters and the output parameters contained in the feedback control equation; and when the value of the loss function reaches the minimum value, solving the target equation to obtain the control matrix.
In some embodiments of the present application, based on the foregoing solution, the feedback control equation comprises:
；
the target equation generated according to the feedback control equation and the state space expression comprises:
wherein the content of the first and second substances,
output parameters representing the integrated model;
is shown to the
Derivation is carried out;
and
coefficients representing the state space expressions, respectively;
input parameters representing the integrated model;
representing the control matrix.
In some embodiments of the present application, based on the foregoing scheme, the loss function constructed based on the input parameters and the output parameters included in the feedback control equation includes:
wherein the content of the first and second substances,
representing the loss function;
to represent
Transposing;
to represent
Transposing;
and
representing a positive definite matrix.
In some embodiments of the present application, based on the foregoing scheme, when the value of the loss function reaches a minimum value, the control matrix satisfies the following equation:
wherein the content of the first and second substances,
to represent
Transposing;
is a solution of the following equation:
wherein the content of the first and second substances,
to represent
Transposing;
is a standard matrix;
to represent
The transposing of (1).
In some embodiments of the present application, based on the foregoing solution, the control unit is configured to: determining a target attitude angle of the self-balancing vehicle, and a target rotation angle and a target angular velocity of the momentum wheel based on the control parameters; controlling a magnitude of current input to the momentum wheel motor based on the target attitude angle, the target rotation angle, and the target angular velocity to control an output torque of the momentum wheel motor.
According to an aspect of embodiments of the present application, there is provided a computer readable medium, on which a computer program is stored, which when executed by a processor, implements a static balance control method of a self-balancing vehicle as described in the above embodiments.
According to an aspect of an embodiment of the present application, there is provided an electronic device including: one or more processors; a storage device for storing one or more programs which, when executed by the one or more processors, cause the one or more processors to implement the method of static balance control for a self-balancing vehicle as described in the above embodiments.
According to an aspect of an embodiment of the present application, there is provided a self-balancing vehicle including: a vehicle body; the momentum wheel motor is used for driving the momentum wheel to rotate; and an electronic device as described in the above embodiments, the electronic device being configured to control the momentum wheel motor.
In the technical solutions provided in some embodiments of the present application, control parameters required for maintaining the self-balancing vehicle in a static balance state are calculated based on a dynamic model of the self-balancing vehicle and a physical model of the momentum wheel motor, a rotation angle of the momentum wheel and an attitude angle of the self-balancing vehicle, and the momentum wheel motor is controlled based on the control parameters, so that the control of the momentum wheel motor of the self-balancing vehicle is realized in a feedback control manner (that is, the rotation angle of the momentum wheel and the attitude angle of the self-balancing vehicle are considered) by using the model as a support, and further, the static balance control of the self-balancing vehicle can be effectively realized, and the stability of the control can be ensured.
It is to be understood that both the foregoing general description and the following detailed description are exemplary and explanatory only and are not restrictive of the application.
Drawings
The accompanying drawings, which are incorporated in and constitute a part of this specification, illustrate embodiments consistent with the present application and together with the description, serve to explain the principles of the application. It is obvious that the drawings in the following description are only some embodiments of the application, and that for a person skilled in the art, other drawings can be derived from them without inventive effort. In the drawings:
FIG. 1 illustrates a side view of a self balancing vehicle of an embodiment of the present application;
FIG. 2 illustrates a top view of a self-balancing vehicle of an embodiment of the present application;
fig. 3 to 5 show an internal structure view of a self-balancing vehicle of the embodiment of the present application;
FIG. 6 illustrates a flow chart of a method of static balance control of a self-balancing vehicle according to one embodiment of the present application;
FIG. 7 illustrates a rear view of a self-balancing vehicle according to one embodiment of the present application;
FIG. 8 illustrates a static balance control process schematic for a self-balancing vehicle according to one embodiment of the present application;
FIG. 9 illustrates a waveform of an attitude angle, an attitude angular velocity, a momentum wheel angle, a momentum wheel angular velocity in simulation results according to an embodiment of the application;
FIG. 10 illustrates a waveform of an input torque of a momentum wheel motor according to an embodiment of the present application;
FIG. 11 illustrates a waveform of an attitude angle, an attitude angular velocity, a momentum wheel angle, a momentum wheel angular velocity in simulation results according to an embodiment of the application;
FIG. 12 illustrates a waveform of an input torque of a momentum wheel motor according to an embodiment of the present application;
FIG. 13 illustrates a block diagram of a static balance control apparatus of a self-balancing vehicle according to one embodiment of the present application;
FIG. 14 illustrates a schematic structural diagram of a computer system suitable for use in implementing the electronic device of an embodiment of the present application.
Detailed Description
Example embodiments will now be described more fully with reference to the accompanying drawings. Example embodiments may, however, be embodied in many different forms and should not be construed as limited to the examples set forth herein; rather, these embodiments are provided so that this disclosure will be thorough and complete, and will fully convey the concept of example embodiments to those skilled in the art.
Furthermore, the described features, structures, or characteristics may be combined in any suitable manner in one or more embodiments. In the following description, numerous specific details are provided to give a thorough understanding of embodiments of the application. One skilled in the relevant art will recognize, however, that the subject matter of the present application can be practiced without one or more of the specific details, or with other methods, components, devices, steps, and so forth. In other instances, well-known methods, devices, implementations, or operations have not been shown or described in detail to avoid obscuring aspects of the application.
The block diagrams shown in the figures are functional entities only and do not necessarily correspond to physically separate entities. I.e. these functional entities may be implemented in the form of software, or in one or more hardware modules or integrated circuits, or in different networks and/or processor means and/or microcontroller means.
The flow charts shown in the drawings are merely illustrative and do not necessarily include all of the contents and operations/steps, nor do they necessarily have to be performed in the order described. For example, some operations/steps may be decomposed, and some operations/steps may be combined or partially combined, so that the actual execution sequence may be changed according to the actual situation.
Artificial Intelligence (AI) is a theory, method, technique and application system that uses a digital computer or a machine controlled by a digital computer to simulate, extend and expand human Intelligence, perceive the environment, acquire knowledge and use the knowledge to obtain the best results. In other words, artificial intelligence is a comprehensive technique of computer science that attempts to understand the essence of intelligence and produce a new intelligent machine that can react in a manner similar to human intelligence. Artificial intelligence is the research of the design principle and the realization method of various intelligent machines, so that the machines have the functions of perception, reasoning and decision making.
The artificial intelligence technology is a comprehensive subject and relates to the field of extensive technology, namely the technology of a hardware level and the technology of a software level. The artificial intelligence infrastructure generally includes technologies such as sensors, dedicated artificial intelligence chips, cloud computing, distributed storage, big data processing technologies, operation/interaction systems, mechatronics, and the like. The artificial intelligence software technology mainly comprises a computer vision technology, a voice processing technology, a natural language processing technology, machine learning/deep learning and the like.
The application provides a static balance control method of self-balancing equipment based on artificial intelligence, which is based on a dynamic model of a self-balancing vehicle and a physical model of a momentum wheel motor, as well as a rotation angle of a momentum wheel and an attitude angle of the self-balancing vehicle, calculates control parameters required for maintaining the self-balancing vehicle in a static balance state, and then controls the momentum wheel motor based on the control parameters, so that the control of the momentum wheel motor of the self-balancing vehicle can be realized in a feedback control mode by using the model as a support, and further the static balance control of the self-balancing vehicle can be effectively realized.
The self-balancing vehicle described herein is intended to feature a device with static self-balancing capabilities, which may be, for example, a self-balancing bicycle, a self-balancing motorcycle, a self-balancing scooter, a self-balancing robot, or other type of device. Embodiments of the present application are not limited by the specific type of self-balancing vehicle and its composition.
FIG. 1 illustrates a side view of a self balancing vehicle of an embodiment of the present application; FIG. 2 illustrates a top view of a self-balancing vehicle of an embodiment of the present application; fig. 3 to 5 show internal structure views of a self-balancing vehicle according to an embodiment of the present application.
Specifically, referring to fig. 1 to 5, a self-balancing vehicle according to an embodiment of the present application may include: frame 100, front handle steering system, rear wheel drive system and balanced momentum wheel system.
The front steering system and the rear wheel driving system are two independent systems, the front steering system is used for controlling the running direction of the self-balancing vehicle, and the rear wheel driving system is used for moving together with the front steering system. The front handle steering system and the rear wheel drive system are respectively connected to the frame 100, and the frame 100 serves to support and connect the front handle steering system and the rear wheel drive system such that the front handle steering system and the rear wheel drive system maintain relatively proper positions. Illustratively, the frame 100 may be a one-piece frame, a trapezoidal frame, a girder frame, or other type of frame, among others. In the illustrative embodiment, the power required by the self-balancing vehicle can be provided by the front handle steering system, the power required by the self-balancing vehicle can also be provided by the rear wheel driving system, and the power required by the self-balancing vehicle can also be provided by the front handle steering system and the rear wheel driving system together.
The balance momentum wheel system is used for maintaining static balance and dynamic balance of the self-balancing vehicle. When the self-balancing vehicle is static, if the vehicle body tilts, the static balance of the self-balancing vehicle can be realized by utilizing the restoring force generated by the balance momentum wheel system and opposite to the tilting direction; when the self-balancing vehicle moves, if the vehicle body tilts, the dynamic balance of the self-balancing vehicle can be realized by utilizing the restoring force which is generated by the front handle steering system and the balance momentum wheel system and is opposite to the tilting direction.
Illustratively, the front handle steering system includes a front wheel 201, a front handle 202, a front handle bearing 203, a front handle motor 204, and a front handle sleeve 205; the rear wheel drive system includes a rear wheel 301, a rear wheel motor 302, and a rear wheel carrier 303. The front handle motor 204 is a member for providing a driving force for the rotation of the front wheel 201, and the rear wheel motor 302 is a member for providing a driving force for the rotation of the rear wheel 301.
The front wheel 202 is sleeved on the front handle 202, the front handle 202 is sleeved on the front handle sleeve 205 through the front handle bearing 203, the front handle motor 204 is fixedly connected with the front handle sleeve 205, and the front handle sleeve 205 is connected with the frame 100; the rear wheel motor 302 is installed in the center of the rear wheel hub, the output shaft of the rear wheel motor 302 is fixedly connected with the rear wheel frame 303, and the rear wheel frame 303 is connected with the frame 100. Illustratively, the front grip sleeve 205 is fixedly connected to the frame 100, and the rear wheel frame 303 is fixedly connected to the frame 100. The angle between the rotation axis of the front handle 202 and the horizontal plane can be adjusted by adjusting the front handle sleeve 205.
In a possible implementation, the center of gravity of the front wheel 201, the center of gravity of the rear wheel 301, the center of gravity of the momentum wheel 401, and the center of gravity of the momentum wheel axle 402 are on a plane, and a vertical plane passing through the center of gravity of the front wheel 201 passes through the center of gravity of the momentum wheel axle 402.
Illustratively, the motor shaft of the front handle motor 204 is coaxial with the rotating shaft of the front handle 202, which is highly integrated and compact.
Illustratively, the self-balancing vehicle further includes a body housing 500, the front handle steering system further includes a front wheel housing 206, and the rear wheel drive system further includes a rear wheel housing 304. The body shell 500 is fixed to the frame 100, the front wheel shell 206 is fixed to the front handle 202, and the rear wheel shell 304 is fixed to the rear wheel frame 303.
The balanced momentum wheel system may comprise: momentum wheel 401, momentum wheel axle 402, momentum wheel bracket 403, adjustable component 404, momentum wheel motor 405, and coupling 406. The momentum wheel 401 is sleeved on the momentum wheel shaft 402, the momentum wheel shaft 402 is sleeved on the momentum wheel support 403, the momentum wheel support 403 is connected with the adjustable component 404, the adjustable component 404 is connected with the frame, the momentum wheel motor 405 is fixedly connected with the momentum wheel support 403, the output shaft of the momentum wheel motor 405 is connected with one end of the coupler 406, and the other end of the coupler 406 is connected with the momentum wheel shaft 402. The coupling 406 is a component that connects two shafts or a shaft and a rotating member, rotates together in the process of transmitting motion and power, and is not disengaged under normal conditions. Illustratively, an attitude sensor is arranged in the self-balancing vehicle, and is used for acquiring the attitude of the self-balancing vehicle, the attitude sensor sends the acquired attitude information to the processor, the processor determines whether the momentum wheel 401 needs to rotate in an acceleration mode or in a deceleration mode according to the attitude information, and sends an acceleration instruction or a deceleration instruction to the momentum wheel motor 405, so that the momentum wheel 401 rotates in an acceleration mode or in a deceleration mode, and the balance of the self-balancing vehicle is maintained.
The momentum wheel axle 402 is arranged in the front-rear direction of the body of the self-balancing vehicle, and the position of the momentum wheel 401 is adjustable in the vertical direction. The adjustment of the position of the momentum wheel 401 is achieved by the up and down movement of the adjustable member 404, as shown in fig. 3, which shows a structure in which the momentum wheel 401 is located below the frame 100, in which case the up and down adjustment of the momentum wheel 401 at the lower side of the frame 100 can be achieved by the adjustable member 404; as shown in fig. 4, which shows a configuration in which the momentum wheel 401 is located above the vehicle frame 100, the up-and-down adjustment of the momentum wheel 401 at the top of the vehicle frame 100 can be achieved by means of an adjustable member 404. Alternatively, the adjustment of the momentum wheel 401 from below the frame 100 to above the frame 100 may also be achieved by means of an adjustable member 404.
Illustratively, one end of momentum wheel axle 402 is directed directly forward of the self-balancing vehicle and the other end of momentum wheel axle 402 is directed directly rearward of the self-balancing vehicle. The front steering system is positioned right in front of the self-balancing vehicle, and the rear wheel drive system is positioned right behind the self-balancing vehicle. Illustratively, the axis of the momentum wheel shaft 402 is located on a horizontal plane and located on a longitudinal section of the self-balancing vehicle, i.e., a straight line where the horizontal plane and the longitudinal section intersect is a straight line where the axis of the momentum wheel shaft 402 is located. The longitudinal section is a plane passing through the center of gravity of the front wheel in the front handle steering system and perpendicular to the horizontal plane.
Alternatively, the adjustable component 404 may be an adjustable lead screw, in which case, the frame 100 may be formed with a threaded hole matching with an external thread of the adjustable lead screw, the adjustable lead screw is connected to a thread on the frame 100 through the threaded hole, and one end of the adjustable lead screw is connected to the momentum wheel bracket 403, for example, the adjustable lead screw may be fixedly connected to the momentum wheel bracket 403 by welding, or the adjustable lead screw may be fixedly connected to the momentum wheel bracket 403 by a detachable connection such as a threaded connection, a snap connection, a hinge connection, or the like.
Alternatively, the adjustable component 404 may be a linear shaft, and the linear shaft refers to a shaft having a linear motion track, and the linear shaft is fixedly connected to the momentum wheel bracket 403, for example, the linear shaft and the momentum wheel bracket 403 may be fixedly connected by welding, or the linear shaft and the momentum wheel bracket 403 may be fixedly connected by a detachable connection such as a threaded connection, a snap connection, a hinge connection, or the like. In this case, the frame 100 may be provided with a linear bearing, and the linear shaft is sleeved with the linear bearing.
Optionally, the momentum wheel bracket 403 is a U-shaped bracket, and the U-shaped bracket includes a first support member and a second support member opposite to each other, and the first support member and the second support member are connected by a connecting portion. The first support component is provided with a first bearing, and the second support component is provided with a second bearing; one end of the momentum wheel shaft 402 is sleeved with a first bearing and the other end of the momentum wheel shaft 402 is sleeved with a second bearing.
Optionally, the connection manner of the momentum wheel 401 and the momentum wheel axle 402 includes any one of the following: spline connection and flat key connection. When the momentum wheel 401 is in splined connection with the momentum wheel shaft 402, an internal spline is formed on the momentum wheel 401, and an external spline matched with the internal spline is formed on the momentum wheel shaft 402; when the momentum wheel 401 is flat-keyed to the momentum wheel axis 402, a key is formed on the momentum wheel 401 and a key slot is formed on the momentum wheel axis 402. The momentum wheel shaft 402 is stressed evenly through spline connection and flat key connection.
In one embodiment of the present application, the momentum wheel 401 generates a restoring torque when rotating at an acceleration or deceleration, and the restoring torqueMCan be calculated by the following formula:M=J·awherein, in the step (A),Jthe moment of inertia of the momentum wheel is represented,ais the angular acceleration. Moment of inertia of momentum wheelJCan be calculated by the following formula:J=mr 2wherein, in the step (A),mwhich is indicative of the mass of the momentum wheel,rindicating radius of momentum wheel, angular accelerationaIs limited by the motor performance when angular acceleration occursaWith a constant magnitude, a moment of inertia is required for the momentum wheel to obtain a greater restoring momentJAnd is larger. Constrained by self-balancing vehicle structure, momentum wheel radiusrShould not be too large, therefore, the momentum wheel massmThe mass distribution of the momentum wheel 401 is not too small, so that the mass distribution of the whole self-balancing vehicle is greatly influenced, and therefore, the selection of the proper installation position of the momentum wheel 401 has important significance for the balance control of the self-balancing vehicle. In the embodiment of the application, the momentum wheel 401 is sleeved on the momentum wheel shaft 402, the momentum wheel shaft 402 is sleeved on the momentum wheel support 403, the momentum wheel support 403 is connected with the adjustable component 404, the position of the momentum wheel 401 can be adjusted by adjusting the adjustable component 404, the position of the momentum wheel 401 can be adjusted in the vertical direction, when the mass or the mass distribution of the self-balancing vehicle changes, the position of the momentum wheel 401 can be adjusted by the adjustable component 404, and the restoring force generated by the momentum wheel 401 can effectively restore the balance of the vehicle body of the self-balancing vehicle.
In addition, the front steering system, the rear wheel driving system and the balance momentum wheel system in the embodiment of the application are independent modules, and the modules are high in independence, strong in expansibility and convenient to install and replace. For example, when the front steering system is damaged, the front steering system can be detached separately for installation and replacement.
Based on the structure of the self-balancing vehicle shown in fig. 1 to 5, the static balance control scheme of the self-balancing vehicle according to the embodiment of the present application is described in detail as follows:
fig. 6 shows a flowchart of a static balance control method for a self-balancing vehicle according to an embodiment of the present application, where an execution subject of the static balance control method may be a processor, such as a processor inside the self-balancing vehicle.
As shown in fig. 6, the static balance control method at least includes the following steps S610 to S640, which are described in detail as follows:
in step S610, a dynamic model configured from dynamic characteristics of the self-balancing vehicle and a physical model configured from physical characteristics of the momentum wheel motor are acquired.
In one embodiment of the present application, the dynamic model of the self-balancing vehicle is intended to characterize the dynamic features of the self-balancing vehicle, such as the number of rigid bodies included therein, the kinematic relationship between the rigid bodies, and the like, and the dynamic model of the self-balancing vehicle may be established based on a model such as a single pendulum model or an inverted pendulum model.
Next, a specific embodiment of establishing a dynamic model and a momentum wheel motor physical model of a self-balancing vehicle is provided. FIG. 7 illustrates a rear view of a self-balancing vehicle according to an embodiment of the present application, as shown in FIG. 7, assuming the self-balancing vehicle is traveling in a horizontal direction and the body direction Oc is at a yaw angle with respect to the gravitational direction Oy, as viewed from the rear to the front of the self-balancing vehicle
(i.e., attitude angle) the height of the center of gravity of the self-balancing vehicle (i.e., the length from the lowest point of the wheels of the self-balancing vehicle to the center of gravity of the vehicle body) is
The height of the momentum wheel (i.e. the distance from the lowest point of the wheel to the position of the momentum wheel) of the self-balancing vehicle is
Setting the rotation angle of the momentum wheel as
。
Assuming that the self-balancing vehicle keeps balance only by means of adjustment of the angular velocity of the momentum wheel in a static state, the parts other than the momentum wheel can be regarded as a whole, in which case the lagrangian (Lagrange) equation shown in the following formula can be applied to the self-balancing vehicle system:
wherein the content of the first and second substances,
the Lagrange operator is represented by the Lagrange operator,qrepresenting a two-dimensional angle vector whose sub-elements are respectively deflection angles
And the rotation angle of the momentum wheel is
，q i Representing two-dimensional vectorsqTo (1)iA wiki element representing a torque vector of the momentum wheel motor, which is also a two-dimensional vector, representing a second one of the torque vectors corresponding to the two-dimensional angle vectoriThe torque of the sub-elements is,iis a positive integer of 1 to 2 inclusive.
And wherein, based on the multi-rigid system of the self-balancing vehicle, a two-dimensional angle vector can be setqThe correspondence relationship with the torque vector of the momentum wheel motor is as follows:
wherein the content of the first and second substances,
representing the torque provided by the momentum wheel motor under negligible friction.
In one embodiment of the present application, based on selfThe kinetic characteristics of the balancing apparatus being derived from the kinetic energy of the balancing vehicle
And potential energy
As shown in the following equation:
wherein the content of the first and second substances,
representing the weight of the self-balancing vehicle except for the momentum wheel;
representing the weight of the momentum wheel;
representing the height of the center of gravity of the self-balancing vehicle;
representing the height of the momentum wheel;
representing the moment of inertia of the self-balancing vehicle except for the momentum wheel;
representing the moment of inertia of the momentum wheel;
representing the aforementioned yaw angle, i.e. attitude angle;
representing the angle of attitude
Obtaining the attitude angular velocity by derivation;
representing the rotation angle of the momentum wheel;
indicating the angle of rotation of the momentum wheel
Deriving the angular velocity of the momentum wheel;
this represents the gravitational acceleration, which may be, for example, 9.8N/kg.
Thereafter, the kinetic energy of the self-balancing vehicle may be calculated
And potential energy
The difference between them, the Lagrange operator is obtained
：
Further, the Lagrange operator can be used
Substituting the aforementioned Lagrangian equation and based on the aforementioned two-dimensional angle vectorqCorresponding relation with torque vector of momentum wheel motor, and converting two-dimensional angle vectorqTwo sub-elements of
And
respectively substituting the Lagrange equation for calculation, and applying linearization treatment, thereby obtaining a dynamic model of the self-balancing vehicle, wherein the dynamic model can be represented by the form of an equation system shown in the following formula (1):
Wherein the content of the first and second substances,
representing the angular velocity of the attitude
Deriving the obtained attitude angular acceleration;
representing angular velocity of the momentum wheel
And (5) obtaining the angular acceleration of the momentum wheel through derivation.
In one embodiment of the present application, the physical model of the momentum wheel motor is intended to characterize the physical motion properties and parameters of the momentum wheel motor, which may be established based on the current, torque, speed relationships of the momentum wheel motor itself, or may be established based on other constituent parameters of the momentum wheel motor or the relationship of the momentum wheel motor to other components in the self-balancing vehicle, for example.
Specifically, a physical characteristic equation set of the momentum wheel motor can be obtained based on the physical characteristics of the momentum wheel motor and the internal parameter relationship thereof, and the physical characteristic equation set is used as the physical model of the momentum wheel motor, as shown in the following formula (2):
wherein the content of the first and second substances,
representing a voltage of the momentum wheel motor;
and
respectively representing the inductance and the resistance of an armature coil of the momentum wheel motor;
representing the current of the momentum wheel motor;
representing a back electromagnetic force of the momentum wheel motor;
indicating the angular velocity of the momentum wheel motor,
；
representing the torque generated by the momentum wheel motor;
representing a motor torque constant;
representing the transmission ratio between the momentum wheel motor and the momentum wheel.
It should be noted that the above embodiments are only intended to provide a method for constructing a dynamic model of a self-balancing vehicle and a physical model of a momentum wheel motor, and the dynamic model of the self-balancing vehicle and the physical model of the momentum wheel motor may also be constructed in other manners.
As shown in fig. 6, in step S620, a rotation angle of the momentum wheel and an attitude angle of the self-balancing vehicle are obtained, where the attitude angle is an angle between a body of the self-balancing vehicle and a gravity direction.
In one embodiment of the present application, the rotation angle of the momentum wheel and the attitude angle of the self-balancing vehicle may be detected by sensors. For example, the detection may be performed by an Inertial Measurement Unit (IMU), a gyroscope, or the like.
In step S630, control parameters required in maintaining the self-balancing vehicle in a static equilibrium state are calculated based on the dynamic model and the physical model, and the rotation angle of the momentum wheel and the attitude angle of the self-balancing vehicle.
In one embodiment of the present application, a dynamic model and a physical model may be fused to generate a comprehensive model for a self-balancing vehicle; and then determining a control matrix for controlling the momentum wheel motor according to the rotation angle of the momentum wheel, the attitude angle of the self-balancing vehicle and the comprehensive model, and further determining control parameters of the momentum wheel motor based on the control matrix.
In an embodiment of the application, when the dynamic model and the physical model are fused, model parameters of the physical model may be transferred to the dynamic model, a first model including physical parameters of the momentum wheel motor is generated, and the first model is used as a comprehensive model for the self-balancing vehicle.
Specifically, for the above formula (2), the reason is that
Much less than
Therefore, the following equation (2) can be omitted
Term, the moment characterization formula shown in the following formula (3) is obtained:
then, the above first model is obtained by substituting equation (3) into the above equation (1), which is expressed by the following equation (4):
wherein the output of the first model
Expressed as:
in one embodiment of the present application, the first model may be converted into the form of a state space equation as shown in the following equation:
wherein the content of the first and second substances,
，
among the above-mentioned parameters,
；
。
in one embodiment of the present application, model parameters of the physical model may be transferred to the dynamic model, a first model including physical parameters of the momentum wheel motor is generated, and then input parameters in the first model are adjusted to a torque of the momentum wheel motor to generate a second model not including the physical parameters of the momentum wheel motor, and the second model is used as a comprehensive model for the self-balancing vehicle. The technical scheme of the embodiment can simplify the parameters of the comprehensive model, and further distinguish the dynamic characteristics of the self-balancing vehicle from the internal characteristics of the momentum wheel motor, so that the influence of the change of the internal parameters of the momentum wheel motor on the output of the comprehensive model of the self-balancing vehicle is ignored, and the simplified second model is shown in the following formula (5):
wherein the output of the second model
Expressed as:
in one embodiment of the present application, the second model may be converted into the form of a state space equation as shown in the following equation:
wherein the content of the first and second substances,
，
among the above-mentioned parameters,
；
。
in an embodiment of the application, after obtaining a comprehensive model corresponding to the self-balancing vehicle (regardless of the first model or the second model, the following scheme may be adopted for processing) and converting the comprehensive model into a state space expression, a target equation for solving a control matrix included in the feedback control equation may be generated according to the feedback control equation and the state space expression, so as to construct a loss function based on input parameters and output parameters included in the feedback control equation, and when a value of the loss function reaches a minimum value, the target equation is solved to obtain the control matrix.
In particular, classical feedback control equations may be applied
Then combining the aforementioned state space equations yields the following target equation:
wherein the content of the first and second substances,
output parameters representing the integrated model;
presentation pair
Derivation is carried out;
and
coefficients representing state space expressions, respectively, with particular reference to the foregoing embodiments;
input parameters representing a composite model;
a control matrix is represented.
In one embodiment of the present application, the following loss function may be introduced:
wherein the content of the first and second substances,
representing a loss function;
to represent
Transposing;
to represent
Transposing;
and
representing a positive definite matrix.
When the value of the aforementioned loss function reaches a minimum value, the control matrix satisfies the following equation:
wherein the content of the first and second substances,
to represent
Transposing;
is a solution of the following equation:
wherein the content of the first and second substances,
to represent
Transposing;
the values of (c) can be referred to the previous embodiment, which is a standard matrix;
to represent
The transposing of (1).
In one embodiment of the present application, after solving for the values of the control matrix, control parameters for the momentum wheel motor may be determined based on the control matrix. For example, a target attitude angle for self-balancing vehicle control, and a target rotation angle and a target angular velocity for momentum wheel control may be determined.
As shown with continued reference to fig. 6, in step S640, the momentum wheel motor is controlled based on the control parameter.
It should be noted that the sequence of steps shown in fig. 6 is only an example, and in other embodiments of the present application, the sequence before the steps may also be exchanged, for example, step S610 and step S620 may be executed simultaneously, or step S620 is executed first, and then step S610 is executed.
In one embodiment of the present application, the magnitude of the current input to the momentum wheel motor may be specifically controlled based on the determined target attitude angle, target rotation angle and target angular velocity to control the output torque of the momentum wheel motor.
The specific control process is shown in fig. 8, where a bicycle module 801 represents a description of a multi-rigid-body dynamic model corresponding to a physical body of a self-balancing vehicle (such as the self-balancing vehicle shown in fig. 1 to 5) -a transfer function, a momentum wheel motor 802 represents a driving module, a momentum wheel speed controller, an attitude controller, an angular speed controller and an adaptive controller represent controller modules, and a sensor measurement and filtering module and a kalman filtering and data fusion module represent data acquisition and filtering modules of a sensor. Wherein, the momentum wheel motor 802 is used for driving a momentum wheel (such as the momentum wheel 401 shown in fig. 3 to 5) of the self-balancing vehicle to rotate; the momentum wheel speed controller is used for controlling the speed of the momentum wheel; the angular velocity controller is used for controlling the angular velocity of the momentum wheel; the attitude controller is used for controlling the attitude of the self-balancing vehicle; the adaptive controller is used for adaptively controlling the self-balancing vehicle to maintain the balance of the self-balancing vehicle, for example, the self-balancing vehicle is already in a balanced state, but the self-balancing vehicle is always found to tilt towards one direction according to the control targets given by the controllers (such as the aforementioned momentum wheel speed controller, attitude controller, angular velocity controller, etc.), so the adaptive controller can give a compensation amount to adaptively adjust the control targets of the controllers to maintain the balance of the self-balancing vehicle.
Shown in FIG. 8
、
And
which represents the reference signal provided by the system, or the reference signal passed to the inner loop after iteration of the outer loop, and, in particular,
a reference rotation angle of the momentum wheel is indicated,
a reference attitude angle of the self-balancing vehicle is shown,
a reference current value is indicated.
In each iteration, the system controls the attitude angle that the desired system is expected to achieve
And adding the output of the adaptive controller, subtracting the attitude angle obtained by Kalman filtering and data fusion, and inputting the difference value to the attitude controller. Output of attitude controller
And the results of the sensor measurement and filtering
Making a difference, inputting the difference into an angular velocity controller, adding the output of the angular velocity controller and the result of the momentum wheel velocity controller to obtain a current reference signal
. The current reference signal
The difference is made with a current feedback signal in the momentum wheel motor 802, the motor torque is output to the momentum wheel motor 802 after passing through the current controller, and the change of the momentum wheel motor torque and the rotation speed drives the posture of the self-balancing vehicle to change. And the attitude angle at the new moment is subjected to sensor measurement and filtering, Kalman filtering and data fusion to serve as a feedback quantity, and participates in the calculation iteration of the control quantity at the next moment. It should be noted that the momentum wheel speed controller, the attitude controller, and the angular velocity shown in fig. 8The feedback mode, the feedback sign and the parameters in the controller are provided by the control matrix K obtained in the above embodiments. The controller parameters of the current control and the self-adaptive control are obtained by debugging according to engineering experience.
In a test scenario of the present application, a role of the calculation result in the system control is given as an example without considering the momentum wheel motor characteristics. Wherein, the actual test and simulation are carried out on the existing bicycle model, and the parameter values in the model are given as follows according to the mass and the size of the actual bicycle body, the mass and the size of the elements such as the momentum wheel and the like and the physical parameters of the motor (all the parameters use international standard units):
acceleration of gravity
= 9.81; mass of components of bicycle other than momentum wheel
= 10; height of momentum wheel
= 0.2; mass of momentum wheel
= 3; height of center of gravity of bicycle frame
= 0.32; radius of momentum wheel
= 0.06; torque constant of motor
= 20.6 × 0.001; back electromagnetic force of motor
= 0.02; motor transmission ratio
= 1; armature coil resistor of motor
= 0.21。
The simulation result of designing the controller according to the above model parameters is shown in fig. 9, in which four waveforms from top to bottom represent: attitude angle, attitude angular velocity, momentum wheel angle, momentum wheel angular velocity.
The waveform of the input torque of the momentum wheel motor is shown in fig. 10, and it can be seen that at the moment of output, the momentum wheel motor needs a very large torque signal, and the signal which exceeds the rated output torque of the momentum wheel motor by many times is likely to cause the motor to be burnt, so that the output torque is usually required to be subjected to amplitude limiting processing in simulation. In practical engineering applications, the transient torque exists for a very short time (< 0.1 s), and the motor performance may not be damaged when the amplitude of the transient torque is within a certain range, which is subject to practical test results and engineering experience.
In the simulation of the embodiment of the application, the moment is not provided with an upper limit and a lower limit, and the controller provides the moment which reaches the stability most quickly. For safety, if the upper and lower torque limits are set to plus or minus 2Nm, the output of the system, i.e., the attitude angle, attitude angular velocity, momentum wheel angle, momentum wheel angular velocity, has a waveform as shown in fig. 11. The waveform of the input torque of the momentum wheel motor is shown in fig. 12.
Note that the input unit of all the moments in the above experiment is Nm. And the simulation result is tested on an actual physical system, the actual test result is qualitatively consistent with the simulation result, the numerical value of the controller parameter is kept consistent in a certain range, the simulation result has great guiding significance for an actual debugging method, and the feasibility and the effectiveness of the design of the controller are verified.
The technical scheme of the embodiment of the application designs the balance controller based on the dynamic model of the self-balancing vehicle with the height-adjustable momentum wheels, and can realize self-balancing of the bicycle in a static state. The balance algorithm is based on a model and is controlled on the premise of being fully familiar with physical properties of the bicycle, a controller derived theoretically can well complete a balance control task in a simulation state, an actual test result is qualitatively consistent with a simulation result in an actual physical system, values of parameters of the controller are kept consistent in a certain range, and feasibility and effectiveness of controller design are further verified.
The following describes embodiments of the apparatus of the present application, which may be used to implement the static balance control method of the self-balancing vehicle in the above embodiments of the present application. For details which are not disclosed in the embodiments of the apparatus of the present application, please refer to the embodiments of the static balance control method of the self-balancing vehicle described above in the present application.
Fig. 13 is a block diagram of a static balance control apparatus of a self-balancing vehicle according to an embodiment of the present application, which is used for controlling the self-balancing vehicle in the above-described embodiment.
Referring to fig. 13, a static balance control apparatus 130 of a self-balancing vehicle according to an embodiment of the present application includes: a first acquisition unit 1302, a second acquisition unit 1304, a processing unit 1306 and a control unit 1308.
Wherein the first obtaining unit 1302 is configured to obtain a dynamic model configured according to dynamic characteristics of the self-balancing vehicle and a physical model configured according to physical characteristics of the momentum wheel motor; a second obtaining unit 1304 configured to obtain a rotation angle of the momentum wheel and an attitude angle of the self-balancing vehicle, where the attitude angle is an included angle between a vehicle body of the self-balancing vehicle and a gravity direction; a processing unit 1306 configured to calculate control parameters required to maintain the self-balancing vehicle in a static equilibrium state based on the dynamic model and the physical model, and a rotation angle of the momentum wheel and an attitude angle of the self-balancing vehicle; a control unit 1308 configured to control the momentum wheel motor based on the control parameter.
In some embodiments of the present application, based on the foregoing scheme, the processing unit 1306 is configured to: fusing the dynamic model and the physical model to generate a comprehensive model for the self-balancing vehicle; determining a control matrix for controlling the momentum wheel motor according to the rotation angle of the momentum wheel, the attitude angle of the self-balancing vehicle and the comprehensive model; determining the control parameter based on the control matrix.
In some embodiments of the present application, based on the foregoing scheme, the processing unit 1306 is configured to:
transferring model parameters of the physical model into the dynamic model, generating a first model containing the physical parameters of the momentum wheel motor, and taking the first model as a comprehensive model for the self-balancing vehicle; or
Transmitting the model parameters of the physical model into the dynamic model, generating a first model containing the physical parameters of the momentum wheel motor, adjusting the input parameters in the first model to the torque of the momentum wheel motor to generate a second model not containing the physical parameters of the momentum wheel motor, and taking the second model as a comprehensive model aiming at the self-balancing vehicle.
In some embodiments of the present application, based on the foregoing scheme, the corresponding equation set of the dynamical model includes:
the system of equations corresponding to the physical model comprises:
transferring model parameters of the physical model into the dynamic model, wherein the generated equation corresponding to the first model comprises:
wherein the content of the first and second substances,
；
；
representing the weight of the self-balancing vehicle except for the momentum wheel;
representing the weight of the momentum wheel;
representing the height of the center of gravity of the self-balancing vehicle;
representing the height of the momentum wheel;
representing the moment of inertia of the self-balancing vehicle except for the momentum wheel;
representing the moment of inertia of the momentum wheel;
representing the attitude angle;
representing the angle of attitude
Obtaining the attitude angular velocity by derivation;
representing the angular velocity of the attitude
Deriving the obtained attitude angular acceleration;
representing the rotation angle of the momentum wheel;
indicating the angle of rotation of the momentum wheel
Deriving the angular velocity of the momentum wheel;
representing angular velocity of the momentum wheel
Deriving the angular acceleration of the momentum wheel;
represents the acceleration of gravity;
representing the torque provided by the momentum wheel motor under the condition of neglecting the friction force;
representing a voltage of the momentum wheel motor;
and
respectively representing the inductance and the resistance of an armature coil of the momentum wheel motor;
representing the current of the momentum wheel motor;
representing a back electromagnetic force of the momentum wheel motor;
indicating the angular velocity of the momentum wheel motor,
；
representing the torque generated by the momentum wheel motor;
representing a motor torque constant;
representing a transmission ratio between the momentum wheel motor and the momentum wheel; the output parameters of the first model comprise
。
In some embodiments of the present application, based on the foregoing scheme, the input parameter in the first model is adjusted to the torque of the momentum wheel motor, and the generated equation corresponding to the second model includes:
wherein the output parameters of the second model comprise
。
In some embodiments of the present application, based on the foregoing solution, the processing unit is configured to: converting the comprehensive model into a state space expression; generating a target equation for solving a control matrix contained in a feedback control equation according to the feedback control equation and the state space expression; constructing a loss function based on the input parameters and the output parameters contained in the feedback control equation; and when the value of the loss function reaches the minimum value, solving the target equation to obtain the control matrix.
In some embodiments of the present application, based on the foregoing solution, the feedback control equation comprises:
；
the target equation generated according to the feedback control equation and the state space expression comprises:
wherein the content of the first and second substances,
output parameters representing the integrated model;
is shown to the
Derivation is carried out;
and
coefficients representing the state space expressions, respectively;
input parameters representing the integrated model;
representing the control matrix.
In some embodiments of the present application, based on the foregoing scheme, the loss function constructed based on the input parameters and the output parameters included in the feedback control equation includes:
wherein the content of the first and second substances,
representing the loss function;
to represent
Transposing;
to represent
Transposing;
and
representing a positive definite matrix.
In some embodiments of the present application, based on the foregoing scheme, when the value of the loss function reaches a minimum value, the control matrix satisfies the following equation:
wherein the content of the first and second substances,
to represent
Transposing;
is a solution of the following equation:
wherein the content of the first and second substances,
to represent
Transposing;
is a standard matrix;
to represent
The transposing of (1).
In some embodiments of the present application, based on the foregoing scheme, the control unit 1308 is configured to: determining a target attitude angle of the self-balancing vehicle, and a target rotation angle and a target angular velocity of the momentum wheel based on the control parameters; controlling a magnitude of current input to the momentum wheel motor based on the target attitude angle, the target rotation angle, and the target angular velocity to control an output torque of the momentum wheel motor.
FIG. 14 illustrates a schematic structural diagram of a computer system suitable for use in implementing the electronic device of an embodiment of the present application.
It should be noted that the computer system 1400 of the electronic device shown in fig. 14 is only an example, and should not bring any limitation to the functions and the scope of use of the embodiments of the present application.
As shown in fig. 14, a computer system 1400 includes a Central Processing Unit (CPU) 1401, which can perform various appropriate actions and processes, such as executing the methods described in the above embodiments, according to a program stored in a Read-Only Memory (ROM) 1402 or a program loaded from a storage portion 1408 into a Random Access Memory (RAM) 1403. In the RAM 1403, various programs and data necessary for system operation are also stored. The CPU 1401, ROM 1402, and RAM 1403 are connected to each other via a bus 1404. An Input/Output (I/O) interface 1405 is also connected to the bus 1404.
The following components are connected to the I/O interface 1405: an input portion 1406 including a keyboard, a mouse, and the like; an output portion 1407 including a Cathode Ray Tube (CRT), a Liquid Crystal Display (LCD), and the like, a speaker, and the like; a storage portion 1408 including a hard disk and the like; and a communication section 1409 including a network interface card such as a LAN (Local area network) card, a modem, or the like. The communication section 1409 performs communication processing via a network such as the internet. The driver 1410 is also connected to the I/O interface 1405 as necessary. A removable medium 1411 such as a magnetic disk, an optical disk, a magneto-optical disk, a semiconductor memory, or the like is mounted on the drive 1410 as necessary, so that a computer program read out therefrom is installed into the storage section 1408 as necessary.
In particular, according to embodiments of the application, the processes described above with reference to the flow diagrams may be implemented as computer software programs. For example, embodiments of the present application include a computer program product comprising a computer program embodied on a computer readable medium, the computer program comprising a computer program for performing the method illustrated by the flow chart. In such an embodiment, the computer program may be downloaded and installed from a network via the communication portion 1409 and/or installed from the removable medium 1411. When the computer program is executed by a Central Processing Unit (CPU) 1401, various functions defined in the system of the present application are executed.
It should be noted that the computer readable medium shown in the embodiments of the present application may be a computer readable signal medium or a computer readable storage medium or any combination of the two. A computer readable storage medium may be, for example, but not limited to, an electronic, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any combination of the foregoing. More specific examples of the computer readable storage medium may include, but are not limited to: an electrical connection having one or more wires, a portable computer diskette, a hard disk, a Random Access Memory (RAM), a Read-Only Memory (ROM), an Erasable Programmable Read-Only Memory (EPROM), a flash Memory, an optical fiber, a portable Compact Disc Read-Only Memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing. In the present application, a computer readable storage medium may be any tangible medium that can contain, or store a program for use by or in connection with an instruction execution system, apparatus, or device. In this application, however, a computer readable signal medium may include a propagated data signal with a computer program embodied therein, for example, in baseband or as part of a carrier wave. Such a propagated data signal may take many forms, including, but not limited to, electro-magnetic, optical, or any suitable combination thereof. A computer readable signal medium may also be any computer readable medium that is not a computer readable storage medium and that can communicate, propagate, or transport a program for use by or in connection with an instruction execution system, apparatus, or device. The computer program embodied on the computer readable medium may be transmitted using any appropriate medium, including but not limited to: wireless, wired, etc., or any suitable combination of the foregoing.
The flowchart and block diagrams in the figures illustrate the architecture, functionality, and operation of possible implementations of systems, methods and computer program products according to various embodiments of the present application. Each block in the flowchart or block diagrams may represent a module, segment, or portion of code, which comprises one or more executable instructions for implementing the specified logical function(s). It should also be noted that, in some alternative implementations, the functions noted in the block may occur out of the order noted in the figures. For example, two blocks shown in succession may, in fact, be executed substantially concurrently, or the blocks may sometimes be executed in the reverse order, depending upon the functionality involved. It will also be noted that each block of the block diagrams or flowchart illustration, and combinations of blocks in the block diagrams or flowchart illustration, can be implemented by special purpose hardware-based systems which perform the specified functions or acts, or combinations of special purpose hardware and computer instructions.
The units described in the embodiments of the present application may be implemented by software, or may be implemented by hardware, and the described units may also be disposed in a processor. Wherein the names of the elements do not in some way constitute a limitation on the elements themselves.
As another aspect, the present application also provides a computer-readable medium, which may be contained in the electronic device described in the above embodiments; or may exist separately without being assembled into the electronic device. The computer readable medium carries one or more programs which, when executed by an electronic device, cause the electronic device to implement the method described in the above embodiments.
It should be noted that although in the above detailed description several modules or units of the device for action execution are mentioned, such a division is not mandatory. Indeed, the features and functionality of two or more modules or units described above may be embodied in one module or unit, according to embodiments of the application. Conversely, the features and functions of one module or unit described above may be further divided into embodiments by a plurality of modules or units.
Through the above description of the embodiments, those skilled in the art will readily understand that the exemplary embodiments described herein may be implemented by software, or by software in combination with necessary hardware. Therefore, the technical solution according to the embodiments of the present application can be embodied in the form of a software product, which can be stored in a non-volatile storage medium (which can be a CD-ROM, a usb disk, a removable hard disk, etc.) or on a network, and includes several instructions to enable a computing device (which can be a personal computer, a server, a touch terminal, or a network device, etc.) to execute the method according to the embodiments of the present application.
Other embodiments of the present application will be apparent to those skilled in the art from consideration of the specification and practice of the embodiments disclosed herein. This application is intended to cover any variations, uses, or adaptations of the invention following, in general, the principles of the application and including such departures from the present disclosure as come within known or customary practice within the art to which the invention pertains.
It will be understood that the present application is not limited to the precise arrangements described above and shown in the drawings and that various modifications and changes may be made without departing from the scope thereof. The scope of the application is limited only by the appended claims.
Claims (15)
1. A static balance control method for a self-balancing vehicle, wherein the self-balancing vehicle comprises a momentum wheel and a momentum wheel motor, the momentum wheel motor is used for driving the momentum wheel to rotate, and the static balance control method comprises the following steps:
acquiring a dynamic model constructed according to the dynamic characteristics of the self-balancing vehicle and a physical model constructed according to the physical characteristics of the momentum wheel motor;
acquiring a rotation angle of the momentum wheel and an attitude angle of the self-balancing vehicle, wherein the attitude angle is an included angle between a vehicle body of the self-balancing vehicle and the gravity direction;
calculating control parameters required for maintaining the self-balancing vehicle in a static balance state based on the dynamic model and the physical model, as well as the rotation angle of the momentum wheel and the attitude angle of the self-balancing vehicle;
controlling the momentum wheel motor based on the control parameter.
2. The method of controlling static balance of a self-balancing vehicle according to claim 1, wherein calculating control parameters required to maintain the self-balancing vehicle in a static balance state based on the dynamic model and the physical model, and the rotation angle of the momentum wheel and the attitude angle of the self-balancing vehicle comprises:
fusing the dynamic model and the physical model to generate a comprehensive model for the self-balancing vehicle;
determining a control matrix for controlling the momentum wheel motor according to the rotation angle of the momentum wheel, the attitude angle of the self-balancing vehicle and the comprehensive model;
determining the control parameter based on the control matrix.
3. The method of claim 2, wherein fusing the dynamic model and the physical model to generate a comprehensive model for the self-balancing vehicle comprises:
transferring model parameters of the physical model into the dynamic model, generating a first model containing the physical parameters of the momentum wheel motor, and taking the first model as a comprehensive model for the self-balancing vehicle; or
Transmitting the model parameters of the physical model into the dynamic model, generating a first model containing the physical parameters of the momentum wheel motor, adjusting the input parameters in the first model to the torque of the momentum wheel motor to generate a second model not containing the physical parameters of the momentum wheel motor, and taking the second model as a comprehensive model aiming at the self-balancing vehicle.
4. The method of claim 3, wherein the system of equations corresponding to the dynamic model comprises:
the system of equations corresponding to the physical model comprises:
transferring model parameters of the physical model into the dynamic model, wherein the generated equation corresponding to the first model comprises:
wherein the content of the first and second substances,
；
；
representing the weight of the self-balancing vehicle except for the momentum wheel;
representing the weight of the momentum wheel;
representing the height of the center of gravity of the self-balancing vehicle;
representing the height of the momentum wheel;
representing the moment of inertia of the self-balancing vehicle except for the momentum wheel;
representing the moment of inertia of the momentum wheel;
representing the attitude angle;
representing the angle of attitude
Obtaining the attitude angular velocity by derivation;
representing the angular velocity of the attitude
Deriving the obtained attitude angular acceleration;
representing the rotation angle of the momentum wheel;
indicating the angle of rotation of the momentum wheel
Deriving the angular velocity of the momentum wheel;
representing angular velocity of the momentum wheel
Deriving the angular acceleration of the momentum wheel;
represents the acceleration of gravity;
representing the torque provided by the momentum wheel motor under the condition of neglecting the friction force;
representing a voltage of the momentum wheel motor;
and
respectively representing the inductance and the resistance of an armature coil of the momentum wheel motor;
representing the current of the momentum wheel motor;
representing a back electromagnetic force of the momentum wheel motor;
indicating the angular velocity of the momentum wheel motor,
；
representing the torque generated by the momentum wheel motor;
representing a motor torque constant;
representing a transmission ratio between the momentum wheel motor and the momentum wheel; the output parameters of the first model comprise
。
5. The method of claim 4, wherein the input parameters in the first model are adjusted to the torque of the momentum wheel motor, and the generated equation corresponding to the second model comprises:
wherein the output parameters of the second model comprise
。
6. The method of controlling static balance of a self-balancing vehicle of claim 2, wherein determining a control matrix for controlling the momentum wheel motor according to the rotation angle of the momentum wheel and the attitude angle of the self-balancing vehicle, and the synthetic model comprises:
converting the comprehensive model into a state space expression;
generating a target equation for solving a control matrix contained in a feedback control equation according to the feedback control equation and the state space expression;
constructing a loss function based on the input parameters and the output parameters contained in the feedback control equation;
and when the value of the loss function reaches the minimum value, solving the target equation to obtain the control matrix.
7. The static balance control method of a self-balancing vehicle of claim 6, wherein the feedback control equation includes:
；
the target equation generated according to the feedback control equation and the state space expression comprises:
wherein the content of the first and second substances,
output parameters representing the integrated model;
is shown to the
Derivation is carried out;
and
coefficients representing the state space expressions, respectively;
input parameters representing the integrated model;
representing the control matrix.
8. The method of claim 7, wherein the loss function constructed based on the input parameters and the output parameters included in the feedback control equation comprises:
wherein the content of the first and second substances,
representing the loss function;
to represent
Transposing;
to represent
Transposing;
and
representing a positive definite matrix.
9. The static balance control method of a self-balancing vehicle of claim 8, wherein the control matrix satisfies the following equation when the value of the loss function reaches a minimum value:
wherein the content of the first and second substances,
to represent
Transposing;
is a solution of the following equation:
wherein the content of the first and second substances,
to represent
Transposing;
is a standard matrix;
to represent
The transposing of (1).
10. The static balance control method of a self-balancing vehicle according to any one of claims 1 to 9, wherein controlling the momentum wheel motor based on the control parameter includes:
determining a target attitude angle of the self-balancing vehicle, and a target rotation angle and a target angular velocity of the momentum wheel based on the control parameters;
controlling a magnitude of current input to the momentum wheel motor based on the target attitude angle, the target rotation angle, and the target angular velocity to control an output torque of the momentum wheel motor.
11. A static balance control apparatus for a self-balancing vehicle, the self-balancing vehicle including a momentum wheel and a momentum wheel motor for driving the momentum wheel to rotate, the static balance control apparatus comprising:
a first acquisition unit configured to acquire a dynamic model configured according to dynamic characteristics of the self-balancing vehicle, and a physical model configured according to physical characteristics of the momentum wheel motor;
a second obtaining unit configured to obtain a rotation angle of the momentum wheel and an attitude angle of the self-balancing vehicle, where the attitude angle is an included angle between a vehicle body of the self-balancing vehicle and a gravity direction;
a processing unit configured to calculate control parameters required to maintain the self-balancing vehicle in a static equilibrium state based on the dynamic model and the physical model, and a rotation angle of the momentum wheel and an attitude angle of the self-balancing vehicle;
a control unit configured to control the momentum wheel motor based on the control parameter.
12. The apparatus of claim 11, wherein the processing unit is configured to:
fusing the dynamic model and the physical model to generate a comprehensive model for the self-balancing vehicle;
determining a control matrix for controlling the momentum wheel motor according to the rotation angle of the momentum wheel, the attitude angle of the self-balancing vehicle and the comprehensive model;
determining the control parameter based on the control matrix.
13. A computer-readable medium, on which a computer program is stored, which, when being executed by a processor, implements a method of static balance control of a self-balancing vehicle according to any one of claims 1 to 10.
14. An electronic device, comprising:
one or more processors;
a storage device for storing one or more programs which, when executed by the one or more processors, cause the one or more processors to implement the static balance control method of a self-balancing vehicle of any one of claims 1 to 10.
15. A self-balancing vehicle, comprising:
a vehicle body;
the momentum wheel motor is used for driving the momentum wheel to rotate; and
the electronic device of claim 14, the electronic device to control the momentum wheel motor.
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