CN114442479A - Balance car control method and device, balance car and computer readable storage medium - Google Patents
Balance car control method and device, balance car and computer readable storage medium Download PDFInfo
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- CN114442479A CN114442479A CN202111677875.1A CN202111677875A CN114442479A CN 114442479 A CN114442479 A CN 114442479A CN 202111677875 A CN202111677875 A CN 202111677875A CN 114442479 A CN114442479 A CN 114442479A
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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
- G05B11/00—Automatic controllers
- G05B11/01—Automatic controllers electric
- G05B11/36—Automatic controllers electric with provision for obtaining particular characteristics, e.g. proportional, integral, differential
- G05B11/42—Automatic controllers electric with provision for obtaining particular characteristics, e.g. proportional, integral, differential for obtaining a characteristic which is both proportional and time-dependent, e.g. P.I., P.I.D.
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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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- 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 application is suitable for the technical field of automatic control, and provides a control method and device of a balance car, the balance car and a storage medium, wherein the control method comprises the following steps: acquiring a first state quantity of the balance car at the current moment; predicting a second state quantity of the balance car at a target moment by adopting a model prediction control algorithm based on the first state quantity and a dynamic model of the balance car, and determining an error between the second state quantity and an expected state quantity of the balance car at the target moment; the second state quantity is related to the first state quantity, thrust borne by the balance car at each control moment and errors, and the related relation forms a preset constraint condition; determining the target thrust borne by the balance car at each control moment when the absolute value of the error is minimum under the condition of meeting the preset constraint condition; carry out drive control to the balance car based on the target thrust that the balance car received at the present moment, can guarantee to carry out drive control to the balance car based on the thrust that determines when the balance car can not lose stability, improved the stability of balance car control.
Description
Technical Field
The application belongs to the technical field of automatic control, and particularly relates to a balance car control method and device, a balance car and a computer readable storage medium.
Background
With the continuous development of automation control technology and the increasing improvement of living standard of people, more and more users select the balance car as a travel tool. The balance car is a typical under-actuated system, which has driving force only at the driving wheel, therefore, the stability control of the balance car is a key problem to be solved, and the stability of the overall inclination angle of the balance car is ensured as much as possible while the moving speed of the balance car is controlled.
In the prior art, a proportional-integral-derivative (PID) control algorithm is usually used to control a balance car, and the method determines the thrust force applied to the balance car at the current time by using the past state quantity and the state quantity of the balance car at the current time. However, the thrust determined based on this method often exceeds the range of the driving force that can be provided by the balance car, and driving control of the balance car based on the thrust determined in this way is likely to cause the balance car to lose stability, reducing the stability of balance car control.
Disclosure of Invention
In view of this, embodiments of the present application provide a method and an apparatus for controlling a balance car, and a computer-readable storage medium, so as to solve the technical problem that an existing method for controlling a balance car easily causes the balance car to lose stability.
In a first aspect, an embodiment of the present application provides a control method for a balance car, including:
acquiring a first state quantity of the balance car at the current moment;
predicting a second state quantity of the balance car at a target moment by adopting a model prediction control algorithm based on the first state quantity and a dynamic model of the balance car, and determining an error between the second state quantity and an expected state quantity of the balance car at the target moment; the second state quantity is related to the first state quantity, thrust borne by the balance car at each control moment and the error, and the related relation forms a preset constraint condition, wherein the control moments comprise the current moment and a plurality of preset moments between the current moment and the target moment;
determining the target thrust borne by the balance car at each control moment when the absolute value of the error is minimum under the condition of meeting the preset constraint condition;
and carrying out drive control on the balance car based on the target thrust borne by the balance car at the current moment.
Optionally, a first time interval is formed between every two adjacent preset moments, the first time interval is formed between the first preset moment and the current moment, and the first time interval is formed between the last preset moment and the target moment; correspondingly, the predicting a second state quantity of the balance car at a target moment by adopting a model predictive control algorithm based on the first state quantity and the dynamic model of the balance car comprises the following steps:
determining a discretization state transition matrix of the balance car according to the dynamic model;
and determining the state quantity and the second state quantity at each preset moment according to the first state quantity and the discretization state transition matrix.
Optionally, the determining a discretized state transition matrix of the balance car according to the dynamic model includes:
determining a state space expression of the balance car according to the dynamic model of the balance car;
and determining the discretization state transition matrix according to the state space expression of the balance car.
Optionally, after determining the state quantity and the second state quantity at each preset time according to the first state quantity and the discretization state transition matrix, the method for controlling the balance car further includes:
and determining the preset constraint condition according to the second state quantity obtained by adopting the discretization state transition matrix and the error.
Optionally, a first time interval is formed between every two adjacent preset moments, the first time interval is formed between the first preset moment and the current moment, and the first time interval is formed between the last preset moment and the target moment; the state quantity of the balance vehicle is described by the position and the speed of the balance vehicle, the pendulum angle of an inverted pendulum of the balance vehicle and the angular velocity of the inverted pendulum;
correspondingly, the predicting a second state quantity of the balance car at a target moment by adopting a model predictive control algorithm based on the first state quantity and the dynamic model of the balance car comprises the following steps:
determining an acceleration expression of the balance car and an angular acceleration expression of the inverted pendulum according to the dynamic model of the balance car;
and according to the acceleration expression and the angular acceleration expression, carrying out recursion by adopting a recursion method to obtain the state quantity of the balance car at each preset moment and the second state quantity.
Optionally, the obtaining, by using a recursion method, the state quantity of the balance car at each preset time and the second state quantity by recursion according to the acceleration expression and the angular acceleration expression includes:
determining a velocity expression of the balance car and an angular velocity expression of the inverted pendulum according to the acceleration expression and the angular acceleration expression;
determining a position expression of the balance vehicle and a swing angle expression of the inverted pendulum according to the speed expression and the angular velocity expression;
and sequentially recursion by adopting a recursion method according to the speed expression, the angular speed expression, the position expression and the swing angle expression to obtain the state quantity of the balance car at each preset moment and the second state quantity.
In a second aspect, an embodiment of the present application provides a control device for a balance car, including:
the first acquisition unit is used for acquiring a first state quantity of the balance car at the current moment;
a first determination unit, configured to predict a second state quantity of the balance car at a target time by using a model predictive control algorithm based on the first state quantity and a dynamic model of the balance car, and determine an error between the second state quantity and an expected state quantity of the balance car at the target time; the second state quantity is related to the first state quantity, thrust borne by the balance car at each control moment and the error, and the related relation forms a preset constraint condition, wherein the control moments comprise the current moment and a plurality of preset moments between the current moment and the target moment;
the second determining unit is used for determining the target thrust borne by the balance car at each control moment when the absolute value of the error is minimum under the condition that the preset constraint condition is met;
and the driving control unit is used for driving and controlling the balance car based on the target thrust borne by the balance car at the current moment.
In a third aspect, an embodiment of the present application provides another control device for a balance car, where the control device for a balance car includes a processor, a memory, and a computer program stored in the memory and executable on the processor, and when the processor executes the computer program, the control device implements the control method for a balance car according to the first aspect or any optional manner of the first aspect.
In a fourth aspect, an embodiment of the present application provides a balance car, including the control device of the balance car of the third aspect.
In a fifth aspect, the present application provides a computer-readable storage medium, where a computer program is stored, and the computer program, when executed by a processor, implements the control method for the balancing vehicle according to the first aspect or any optional manner of the first aspect.
In a sixth aspect, the present application provides a computer program product, when the computer program product runs on a balance car, the balance car is caused to execute the method for controlling the balance car according to the first aspect or any optional manner of the first aspect.
The implementation of the control method and device of the balance car, the computer readable storage medium and the computer program product provided by the embodiment of the application has the following beneficial effects:
according to the control method of the balance car, the first state quantity of the balance car at the current moment is obtained, the second state quantity of the balance car at the target moment is predicted by adopting a model prediction control algorithm based on the first state quantity and a dynamic model of the balance car, the error between the second state quantity and the expected state quantity of the balance car at the target moment is determined, the target thrust borne by the balance car at each control moment when the absolute value of the error is minimum under the condition that the preset constraint condition is met is determined, and the drive control of the balance car is performed based on the target thrust borne by the balance car at the current moment. Because the second state quantity and the first state quantity, the thrust that the balance car receives at each control moment and the correlation between the error constitute the preset constraint condition, consequently adopt the thrust that the model prediction mode was confirmed that the balance car received in the driving force scope that the balance car can provide to can guarantee that the balance car can not lose stably when carrying out drive control to the balance car based on the thrust that confirms, improved the stability of balance car control.
Drawings
In order to more clearly illustrate the technical solutions in the embodiments of the present application, the drawings needed to be used in the embodiments or the prior art descriptions will be briefly described below, and it is obvious that the drawings in the following description are only some embodiments of the present application, and it is obvious for those skilled in the art to obtain other drawings based on these drawings without inventive exercise.
Fig. 1 is a schematic structural diagram of an inverted pendulum model of a trolley provided in an embodiment of the present application;
fig. 2 is a schematic flowchart of a control method of a balance car according to an embodiment of the present disclosure;
fig. 3 is a flowchart illustrating a specific implementation of S22 in a control method of a balance car according to an embodiment of the present application;
fig. 4 is a flowchart illustrating a specific implementation of S22 in a control method of a balance car according to another embodiment of the present application;
fig. 5 is a schematic structural diagram of a control device of a balance car according to an embodiment of the present disclosure;
fig. 6 is a schematic structural diagram of a control device of a balance car according to another embodiment of the present application.
Detailed Description
It is noted that the terminology used in the description of the embodiments of the present application is for the purpose of describing particular embodiments of the present application only and is not intended to be limiting of the present application. In the description of the embodiments of the present application, "/" means "or" unless otherwise specified, for example, a/B may mean a or B; "and/or" herein is merely an associative relationship describing an association, meaning that there may be three relationships, e.g., a and/or B, may mean: a exists alone, A and B exist simultaneously, and B exists alone. In addition, in the description of the embodiments of the present application, "a plurality" means two or more than two, "at least one", "one or more" means one, two or more than two, unless otherwise specified.
In the following, the terms "first", "second" are used for descriptive purposes only and are not to be understood as indicating or implying relative importance or implicitly indicating the number of technical features indicated. Thus, a definition of "a first" or "a second" feature may explicitly or implicitly include one or more of the features.
Reference throughout this specification to "one embodiment" or "some embodiments," or the like, means that a particular feature, structure, or characteristic described in connection with the embodiment is included in one or more embodiments of the present application. Thus, appearances of the phrases "in one embodiment," "in some embodiments," "in other embodiments," or the like, in various places throughout this specification are not necessarily all referring to the same embodiment, but rather "one or more but not all embodiments" unless specifically stated otherwise. The terms "comprising," "including," "having," and variations thereof mean "including, but not limited to," unless expressly specified otherwise.
The control method of the balance car provided by the embodiment of the application is applied to the balance car, including but not limited to a single-wheel balance car or a double-wheel balance car. The inside of balance car can be provided with the controlling means of balance car. In the embodiment of the application, the execution main body of the control method of the balance car is a control device of the balance car. The target script file is configured for the control device of the balance car, and the target script file describes the control method of the balance car provided by the embodiment of the application, so that the control device of the balance car executes the target script file when driving and controlling the balance car, and further executes each step in the control method of the balance car provided by the embodiment of the application.
The balance vehicle can be generally simplified into a vehicle inverted pendulum model. Please refer to fig. 1, which is a schematic structural diagram of an inverted pendulum model of a vehicle according to an embodiment of the present disclosure. As shown in fig. 1, the inverted pendulum model of the vehicle may include an inverted pendulum 11 and a vehicle 12. The inverted pendulum 11 and the vehicle 12 can be connected by a hinge by controlling the thrust to the vehicle 12
The swing angle θ of the inverted pendulum 11 and the position of the vehicle can be controlled.
Based on this, the dynamic model of the balance car can be expressed as:
wherein M is the mass of the trolley 12, M is the mass of the inverted pendulum 11,
is the acceleration of the vehicle 12 (i.e., the balance car), l is the length of the inverted pendulum 11, and θ is the swing angle of the inverted pendulum 11 (i.e., the inverted pendulumThe angle of the pendulum 11 off the vertical),
in order to be the angular velocity of the inverted pendulum 11,
the angular acceleration of the inverted pendulum 11, J the moment of inertia of the inverted pendulum 11 about the hinge, g the acceleration of gravity, and u the thrust to which the vehicle 12 (i.e., the balance car) is subjected.
In the embodiment of the application, the state quantity of the balance car can be defined as:
wherein x is the position of the balance car (i.e. the trolley 12),
to balance the speed of the vehicle.
The following describes in detail a control method of a balance vehicle according to an embodiment of the present application.
Please refer to fig. 2, which is a schematic flowchart illustrating a control method of a balance car according to an embodiment of the present application. As shown in fig. 2, the control method of the balance car may include S21 to S24, which are detailed as follows:
s21: and acquiring a first state quantity of the balance car at the current moment.
The current time may be any one time during the movement of the balancing vehicle, that is, at each time during the movement of the balancing vehicle, the control device of the balancing vehicle executes S21 to S24 in the embodiment of the present application.
The first state quantity can be described by the position, the velocity, the pendulum angle of the inverted pendulum of the balance vehicle, and the angular velocity of the inverted pendulum of the balance vehicle at the present time. The position and the speed of the balance vehicle at the current moment, the swing angle of the inverted pendulum of the balance vehicle and the angular speed of the inverted pendulum can be acquired by a sensor in the balance vehicle.
For example, if the current time is time k, the first state quantity is:
wherein s iskIs a first state quantity, xkTo balance the position of the vehicle at time k,
to balance the speed of the vehicle at time k, θkIn order to balance the swing angle of the vehicle at the moment k,
to balance the angular velocity of the vehicle at time k.
S22: and predicting a second state quantity of the balance vehicle at a target moment by adopting a model prediction control algorithm based on the first state quantity and a dynamic model of the balance vehicle, and determining an error between the second state quantity and an expected state quantity of the balance vehicle at the target moment.
The target time may be any time after the current time. The time interval between the target time and the current time may be set according to actual requirements, and is not particularly limited herein.
The second state quantity is related to the first state quantity of the balance car at the current moment, the thrust borne by the balance car at each control moment, and the error between the second state quantity of the balance car at the target moment and the expected state quantity of the balance car at the target moment, and the related relation among the first state quantity, the thrust borne by the balance car at the current moment, the thrust borne by the balance car at the target moment and the expected state quantity of the balance car at the target moment forms a preset constraint condition.
The control time comprises a current time and a plurality of preset times between the current time and a target time. The number of the preset time instants can be set according to actual requirements, and is not particularly limited herein.
Illustratively, if the current time is k, the time interval between the target time and the current time is TsIf the target time is k + TsThe time of day. If N-1 are included between the current time and the target timeThe N-1 preset moments may be, respectively, a preset time interval, where a time interval between the first preset moment and the current moment is equal to a time interval between every two adjacent preset moments, and a time interval between the last preset moment and the target moment is also equal to a time interval between every two adjacent preset moments:
k+Ts/N,k+2*Ts/N,...,(N-1)k+Ts/N。
i.e. the interval T between every two adjacent preset momentssN, the interval T between the current time and the first preset timesN, the interval T between the N-1 st preset time and the target times/N。
For convenience of description, the N-1 preset time instants may be represented by an order of the N-1 preset time instants, for example, the first preset time instant may be represented as k +1, and then the N-1 preset time instants may be simplified as follows:
k+1,k+2,...,k+N-1。
then, the respective control times are:
k,k+1,k+2,...,k+N-1。
the thrust force of the balance car at each control moment can be represented as:
[uk uk+1...uk+N-1]T。
in one embodiment of the present application, the Model Predictive Control algorithm may be a Model Predictive Control (MPC) algorithm. Based on this, the step of predicting the second state quantity of the balance vehicle at the target time by using the model predictive control algorithm based on the first state quantity and the dynamic model of the balance vehicle can be realized by S221 to S222 shown in fig. 3, which are detailed as follows:
s221: and determining a discretization state transition matrix of the balance car according to the dynamic model.
In this embodiment, the discretized state transition matrix can be determined by the following two steps:
step 1: and determining a state space expression of the balance car according to the dynamic model of the balance car.
Step 2: and determining the discretization state transition matrix according to the state space expression of the balance car.
Specifically, the dynamic model of the balance car may be linearized at the equilibrium position to obtain a linearized equation of the dynamic model of the balance car at the equilibrium position, as follows:
the balance position refers to a position where the swing angle θ of the inverted pendulum of the balance vehicle is equal to 0, that is, a position where the inverted pendulum of the balance vehicle is in the vertical direction.
The state quantity of the balance car is
Therefore, the state space expression of the balance car can be obtained according to the state quantity of the balance car as follows:
wherein the content of the first and second substances,
is a state space expression of the balance car.
In this embodiment, for convenience of description, the state space expression of the balance car may be simplified to order
Then it is possible to obtain:
in this embodiment, after the state space expression of the balance car is obtained, the state transition equation of the balance car may be determined based on the state space expression of the balance car, and then the discretization state transition matrix of the balance car may be determined according to the state transition equation of the balance car.
By way of example and not limitation, the state transition equations of the balance car may be determined according to the forward Eulerian method.
Specifically, the state space expression of the balance car can be further expressed as:
wherein s (k +1) is the state quantity of the balance vehicle at the moment k +1, and s (k) is the state quantity of the balance vehicle at the moment k.
Thus, it is possible to obtain:
converting equation (1) can yield:
s(k+1)＝(I+Ts/N*A)s(k)+Ts/N*Bu(k)。
wherein, I is a unit matrix, and u (k) is the thrust borne by the balance car at the moment k.
The order of I is the same as the number of parameters in the state quantity of the balance car. In this embodiment, since the state quantity of the balance car includes 4 parameters, I is a fourth-order identity matrix.
In addition
Then the state transition equation of the balance car can be obtained as follows:
according to the state transition equation of the balance car, the discretization state transition matrix of the balance car can be obtained as follows:
wherein S isk+1State quantity of balance car at the moment of k +1, skFor balancing the state quantity of the vehicle at time k, ukThe thrust borne by the balance car at the moment k is obtained.
S222: and determining the state quantity and the second state quantity at each preset moment according to the first state quantity and the discretization state transition matrix.
In this embodiment, it is assumed that the thrust exerted on the balance car at each control time is
[uk uk+1 ... uk+N-1]T；
Then, according to the first state quantity and the discretization state transition matrix of the balance car, the state quantity of the balance car at each preset time and the state quantity of the balance car at the target time can be obtained as follows:
s (k +1) is the state quantity of the balance car at the first preset time, S (k +2) is the state quantity of the balance car at the second preset time, and so on, and S (k + N-1) is the state quantity of the balance car at the N-1 th preset time. And S (k + N) is a second state quantity of the balance car at the target time.
The thrust force applied to the balance car at each time is an unknown quantity, and it is necessary to obtain the thrust force from S21 to S23 of the present application.
In the embodiment of the application, the expected state quantity of the balance car at each moment in the motion process can be preset. The preset expected state quantities of the balance car at various moments in the moving process can be stored in a local memory of the balance car. The control device of the balance car can acquire the expected state quantity of the balance car at the target moment from the local memory of the balance car.
Then, the second state quantity of the balance car at the target time and the expected state quantity of the balance car at the target time may be differentiated to obtain an error between the two, that is, the error between the two may be expressed as:
w＝Sd-S (k + N) formula (3)
Wherein w is the error between the second state quantity of the balance vehicle at the target time and the expected state quantity of the balance vehicle at the target time, SdS (k + N) is a desired state quantity of the balance car at the target time.
Since the state quantity of the balance vehicle is described by the position, velocity, pendulum angle of the inverted pendulum, and angular velocity of the inverted pendulum of the balance vehicle, the error between the second state quantity of the balance vehicle and the desired state quantity of the balance vehicle at the target time can also be expressed as:
w＝[w1 w2 w3 w4]T；
wherein, w1For the error between the actual position of the balancing vehicle at the target moment and the desired position of the balancing vehicle at the target moment, w2For the error between the actual speed of the balancing vehicle at the target moment and the desired speed of the balancing vehicle at the target moment, w3W is an error between an actual swing angle of the inverted pendulum at a target time and a desired swing angle of the inverted pendulum at the target time4Is the error between the actual angular velocity of the inverted pendulum at the target moment for the balance vehicle and the desired angular velocity of the inverted pendulum at the target moment for the balance vehicle.
In an embodiment of the present application, when the MPC algorithm is used to determine the target thrust that the balance car is subjected to at each control time, the preset constraint condition may be determined according to the second state quantity of the balance car at the target time (i.e. formula (2)) obtained by using the discretization state transition matrix and an error between the second state quantity and the expected state quantity at the target time (i.e. formula (3)), that is, the following preset constraint conditions may be obtained according to formula (2) and formula (3):
s23: and determining the target thrust borne by the balance car at each control moment when the absolute value of the error is minimum under the condition of meeting the preset constraint condition.
In the embodiment of the present application, since the error between the second state quantity of the balance vehicle at the target time and the desired state quantity of the balance vehicle at the target time may be a positive value or a negative value, the smaller the absolute value of the error or the square of the error, the closer the second state quantity and the desired state quantity to each other.
It can be understood that the problem of determining the target thrust to which the balance vehicle is subjected at each control moment when the absolute value of the error is minimum under the condition that the preset constraint condition is met is a quadratic programming problem.
Based on this, in one embodiment of the present application, when the MPC algorithm is adopted to determine the target thrust to which the balance car is subjected at each control moment, the following equation can be obtained through a standard form of quadratic programming:
in this embodiment, a quadratic programming solver may be used to solve the equation, so as to obtain the target thrust exerted on the balance car at each control time.
S24: and carrying out drive control on the balance car based on the target thrust borne by the balance car at the current moment.
In the embodiment of the application, after the target thrust borne by the balance car at each control moment is obtained, the balance car can be subjected to drive control according to the target thrust borne by the balance car at the current moment.
As can be seen from the above, in the control method of the balance car provided in this embodiment, the first state quantity of the balance car at the current time is obtained, the second state quantity of the balance car at the target time is predicted by using the model prediction control algorithm based on the first state quantity and the dynamic model of the balance car, the error between the second state quantity and the expected state quantity of the balance car at the target time is determined, the target thrust applied to the balance car at each control time when the absolute value of the error is minimum under the condition that the preset constraint condition is satisfied is determined, and the drive control of the balance car is performed based on the target thrust applied to the balance car at the current time. Because the second state quantity and the first state quantity, the thrust that the balance car receives at each control moment and the correlation between the error constitute the preset constraint condition, the thrust that the balance car received that consequently adopts the mode of model prediction to confirm is in the scope of the drive power that the balance car can provide to can guarantee that the balance car can not lose stably when carrying out drive control to the balance car based on the thrust that confirms, thereby has improved the stability of balance car control.
In addition, the dynamic model of the balance car is subjected to linearization processing near the balance position, so that the control algorithm of the balance car can be simplified, and the stability of the balance car near the balance position can be improved.
However, if the balance car deviates far from the balance position, the above method cannot ensure that the balance car is still in a stable state, that is, the stability of the balance car near the balance position can be ensured by using the linear model predictive control algorithm, and the stability of the balance car when the balance car deviates from the balance position cannot be ensured. Based on this, in another embodiment of the present application, a Nonlinear Model Predictive Control (NMPC) algorithm may be used to determine the thrust force exerted by the balance car at each control instant.
Referring to fig. 4, a schematic flowchart of a control method of a balance car according to another embodiment of the present application is provided. As shown in fig. 3, the present embodiment is different from the embodiments corresponding to fig. 2 to 3 in that S22 in the present embodiment includes S223 to S224, which are detailed as follows:
s223: and determining an acceleration expression of the balance vehicle and an angular acceleration expression of the inverted pendulum according to the dynamic model of the balance vehicle.
In this embodiment, the acceleration expression of the balance car and the angular acceleration expression of the inverted pendulum may be obtained by deforming the dynamic model of the balance car as follows:
s224: and according to the acceleration expression and the angular acceleration expression, carrying out recursion by adopting a recursion method to obtain the state quantity of the balance car at each preset moment and the second state quantity.
In a possible implementation manner, the determining the second state quantity of the balance car at the target time by using a recurrence method may specifically include the following steps:
step 1: and determining a velocity expression of the balance car and an angular velocity expression of the inverted pendulum according to the acceleration expression and the angular acceleration expression.
Step 2: and determining a position expression of the balance vehicle and a swing angle expression of the inverted pendulum according to the speed expression and the angular speed expression.
And step 3: and sequentially recursion by adopting a recursion method according to the speed expression, the angular speed expression, the position expression and the swing angle expression to obtain the state quantity of the balance car at each preset moment and the second state quantity.
In this embodiment, as can be seen from the formula (4), the expressions of the acceleration of the balance car at each preset time and target time and the expressions of the angular acceleration of the inverted pendulum are as follows:
then, the velocity expressions of the balance car at the respective preset times and the target time and the angular velocity expression of the inverted pendulum may be respectively as follows:
the position expression of the balance vehicle at each preset time and target time and the swing angle expression of the inverted pendulum may be respectively as follows:
the control device of the balance car may sequentially recur the state quantities of the balance car at the timings k +1, k +2, …, k + N-1, and k + N based on the above equation (5), equation (6), and equation (7) from the timing k + 1. Then, the balance car is at k + TsThe second state quantity at the time (i.e., the target time) can be expressed as:
in this embodiment, since the relationship between the state quantity of the balance car and the thrust force applied to the balance car cannot be expressed by a specific relational expression, the relationship between the state quantity of the balance car and the thrust force applied to the balance car is expressed by the function si(u) based on which the preset constraint may be si(u) is not less than 0. The following equation can be obtained from the standard form of quadratic programming:
solving the equation by adopting a quadratic programming solver to obtain the target thrust borne by the balance car at each control moment.
As can be seen from the above, the control method for the balance car provided in this embodiment adopts a nonlinear model prediction mode, which can not only improve the stability of the balance car near the equilibrium position, but also improve the stability of the balance car near the non-equilibrium position, that is, can implement global stability control on the balance car.
It should be understood that, the sequence numbers of the steps in the foregoing embodiments do not imply an execution sequence, and the execution sequence of each process should be determined by its function and inherent logic, and should not constitute any limitation to the implementation process of the embodiments of the present application.
Based on the control method of the balance car provided by the embodiment, the embodiment of the invention further provides an embodiment of the control device of the balance car for realizing the embodiment of the method. Please refer to fig. 5, which is a schematic structural diagram of a control device of a balance car according to an embodiment of the present application. For convenience of explanation, only the portions related to the present embodiment are shown. As shown in fig. 5, the control device 50 of the balance car may include: a first acquisition unit 51, a first determination unit 52, a second determination unit 53, and a drive control unit 54. Wherein:
the first obtaining unit 51 is configured to obtain a first state quantity of the balance car at the current time.
The first determination unit 52 is configured to predict a second state quantity of the balance vehicle at a target time by using a model predictive control algorithm based on the first state quantity and a dynamic model of the balance vehicle, and determine an error between the second state quantity and an expected state quantity of the balance vehicle at the target time; the second state quantity is related to the first state quantity, the thrust borne by the balance car at each control moment and the error, the related relation forms a preset constraint condition, and the control moments comprise the current moment and a plurality of preset moments between the current moment and the target moment.
The second determining unit 53 is configured to determine a target thrust that the balance car receives at each of the control moments when the absolute value of the error is minimum under the condition that the preset constraint condition is satisfied.
The driving control unit 54 is configured to perform driving control on the balance car based on the target thrust that the balance car receives at the current time.
Optionally, a first time interval is formed between every two adjacent preset moments, the first time interval is formed between the first preset moment and the current moment, and the first time interval is formed between the last preset moment and the target moment; correspondingly, the first determination unit 52 includes a state transition matrix determination unit and a state quantity determination unit. Wherein:
the state transition matrix determining unit is used for determining the discretization state transition matrix of the balance car according to the dynamic model.
The state quantity determining unit is used for determining the state quantity and the second state quantity at each preset moment according to the first state quantity and the discretization state transition matrix.
Optionally, the state transition matrix determining unit is specifically configured to:
determining a state space expression of the balance car according to the dynamic model of the balance car;
and determining the discretization state transition matrix according to the state space expression of the balance car.
Optionally, the control device 50 of the balance vehicle further includes a third determination unit.
The third determining unit is configured to determine the preset constraint condition according to the second state quantity obtained by using the discretization state transition matrix and the error.
Optionally, a first time interval is formed between every two adjacent preset moments, the first time interval is formed between the first preset moment and the current moment, and the first time interval is formed between the last preset moment and the target moment; the state quantity of the balance vehicle is described by the position and the speed of the balance vehicle, the pendulum angle of an inverted pendulum of the balance vehicle and the angular velocity of the inverted pendulum;
correspondingly, the first determining unit 52 includes an expression determining unit and a recurrence unit. Wherein:
the expression determining unit is used for determining an acceleration expression of the balance vehicle and an angular acceleration expression of the inverted pendulum according to the dynamic model of the balance vehicle.
And the recursion unit is used for recurrently obtaining the state quantity of the balance car at each preset moment and the second state quantity by adopting a recursion method according to the acceleration expression and the angular acceleration expression.
Optionally, the recurrence unit is specifically configured to:
determining a velocity expression of the balance car and an angular velocity expression of the inverted pendulum according to the acceleration expression and the angular acceleration expression;
determining a position expression of the balance vehicle and a swing angle expression of the inverted pendulum according to the speed expression and the angular velocity expression;
and sequentially recursion by adopting a recursion method according to the speed expression, the angular speed expression, the position expression and the swing angle expression to obtain the state quantity of the balance car at each preset moment and the second state quantity.
It should be noted that, for the information interaction, the execution process, and other contents between the above units, the specific functions and the technical effects brought by the method embodiments of the present application are based on the same concept, and specific reference may be made to the method embodiment part, which is not described herein again.
It will be clear to those skilled in the art that, for convenience and simplicity of description, the above-mentioned division of the functional units is merely illustrated, and in practical applications, the above-mentioned function distribution may be performed by different functional units according to needs, that is, the internal structure of the control device of the balance car is divided into different functional units to perform all or part of the above-mentioned functions. Each functional unit in the embodiments may be integrated into one processing unit, or each unit may exist alone physically, or two or more units are integrated into one unit, and the integrated unit may be implemented in a form of hardware, or in a form of software functional unit. In addition, specific names of the functional units are only used for distinguishing one functional unit from another, and are not used for limiting the protection scope of the application. The specific working process of the units in the system may refer to the corresponding process in the foregoing method embodiment, and is not described herein again.
Referring to fig. 6, fig. 6 is a schematic structural diagram of a control device of a balance car according to an embodiment of the present application. As shown in fig. 6, the control device 6 of the balance car provided in this embodiment may include: a processor 60, a memory 61 and a computer program 62 stored in the memory 61 and operable on the processor 60, for example a program corresponding to a control method of a balancing vehicle. The processor 60, when executing the computer program 62, implements the steps in the embodiment of the control method for the balancing vehicle described above, such as S21-S24 shown in fig. 2. Alternatively, the processor 60, when executing the computer program 62, implements the functions of the modules/units in the control device embodiment of the balancing vehicle, such as the functions of the units 51-54 shown in fig. 5.
Illustratively, the computer program 62 may be divided into one or more modules/units, which are stored in the memory 61 and executed by the processor 60 to accomplish the present application. One or more of the modules/units may be a series of computer program instruction segments capable of performing specific functions for describing the execution of the computer program 62 in the control device 6 of the balance vehicle. For example, the computer program 62 may be divided into a first obtaining unit, a first determining unit, a second determining unit and a driving control unit, and the functions of each unit are described with reference to the related description in the embodiment corresponding to fig. 5, which is not repeated herein.
Those skilled in the art will appreciate that fig. 6 is merely an example of the control device 6 of the balance car, and does not constitute a limitation of the control device 6 of the balance car, and may include more or less components than those shown, or some components in combination, or different components.
The processor 60 may be a Central Processing Unit (CPU), other general purpose processor, a Digital Signal Processor (DSP), an Application Specific Integrated Circuit (ASIC), an off-the-shelf programmable gate array (FPGA) or other programmable logic device, discrete gate or transistor logic, discrete hardware components, etc. A general purpose processor may be a microprocessor or the processor may be any conventional processor or the like.
The memory 61 may be an internal storage unit of the control device 6 of the balance vehicle, such as a hard disk or a memory of the control device 6 of the balance vehicle. The memory 61 may also be an external storage device of the control device 6 of the balance vehicle, such as a plug-in hard disk, a Smart Memory Card (SMC), a Secure Digital (SD) card, or a flash memory card (flash card) provided on the control device 6 of the balance vehicle. Further, the memory 61 may also include both an internal memory unit and an external memory device of the control device 6 of the balance vehicle. The memory 61 is used for storing computer programs and other programs and data required for the control device of the balance car. The memory 61 may also be used to temporarily store data that has been output or is to be output.
The embodiment of the application also provides a balance car which can comprise the control device of the balance car in the embodiment corresponding to the figure 5 or the figure 6.
The embodiments of the present application further provide a computer-readable storage medium, in which a computer program is stored, and when the computer program is executed by a processor, the steps in the above-mentioned method embodiments can be implemented.
The embodiments of the present application provide a computer program product, which, when running on a control device of a balance car, causes the control device of the balance car to execute the steps in the above-mentioned method embodiments.
In the above embodiments, the description of each embodiment has its own emphasis, and parts that are not described or illustrated in a certain embodiment may refer to the description of other embodiments.
Those of ordinary skill in the art will appreciate that the various illustrative elements and algorithm steps described in connection with the embodiments disclosed herein may be implemented as electronic hardware or combinations of computer software and electronic hardware. Whether such functionality is implemented as hardware or software depends upon the particular application and design constraints imposed on the implementation. Skilled artisans may implement the described functionality in varying ways for each particular application, but such implementation decisions should not be interpreted as causing a departure from the scope of the present application.
The above-mentioned embodiments are only used for illustrating the technical solutions of the present application, and not for limiting the same; although the present application has been described in detail with reference to the foregoing embodiments, it should be understood by those of ordinary skill in the art that: the technical solutions described in the foregoing embodiments may still be modified, or some technical features may be equivalently replaced; such modifications and substitutions do not substantially depart from the spirit and scope of the embodiments of the present application and are intended to be included within the scope of the present application.
Claims (10)
1. A control method of a balance car is characterized by comprising the following steps:
acquiring a first state quantity of the balance car at the current moment;
predicting a second state quantity of the balance car at a target moment by adopting a model prediction control algorithm based on the first state quantity and a dynamic model of the balance car, and determining an error between the second state quantity and an expected state quantity of the balance car at the target moment; the second state quantity is related to the first state quantity, thrust borne by the balance car at each control moment and the error, and the related relation forms a preset constraint condition, wherein the control moments comprise the current moment and a plurality of preset moments between the current moment and the target moment;
determining the target thrust borne by the balance car at each control moment when the absolute value of the error is minimum under the condition of meeting the preset constraint condition;
and carrying out drive control on the balance car based on the target thrust borne by the balance car at the current moment.
2. The control method of the balance car according to claim 1, wherein a first time period is spaced between every two adjacent preset moments, the first time period is spaced between the first preset moment and the current moment, and the first time period is spaced between the last preset moment and the target moment; correspondingly, the predicting a second state quantity of the balance car at a target moment by adopting a model predictive control algorithm based on the first state quantity and the dynamic model of the balance car comprises the following steps:
determining a discretization state transition matrix of the balance car according to the dynamic model;
and determining the state quantity and the second state quantity at each preset moment according to the first state quantity and the discretization state transition matrix.
3. The method for controlling the balance vehicle according to claim 2, wherein the determining the discretized state transition matrix of the balance vehicle according to the dynamic model includes:
determining a state space expression of the balance car according to the dynamic model of the balance car;
and determining the discretization state transition matrix according to the state space expression of the balance car.
4. The control method of a balance vehicle according to claim 2, wherein after determining the state quantity and the second state quantity at each of the preset times from the first state quantity and the discretized state transition matrix, the control method of a balance vehicle further comprises:
and determining the preset constraint condition according to the second state quantity obtained by adopting the discretization state transition matrix and the error.
5. The control method of the balance car according to any one of claims 1 to 4, wherein a first time period is arranged between every two adjacent preset times, the first time period is arranged between the first preset time and the current time, and the first time period is arranged between the last preset time and the target time; the state quantity of the balance vehicle is described by the position and the speed of the balance vehicle, the pendulum angle of an inverted pendulum of the balance vehicle and the angular velocity of the inverted pendulum;
correspondingly, the predicting a second state quantity of the balance vehicle at a target moment by using a model predictive control algorithm based on the first state quantity and the dynamic model of the balance vehicle comprises the following steps:
determining an acceleration expression of the balance car and an angular acceleration expression of the inverted pendulum according to the dynamic model of the balance car;
and according to the acceleration expression and the angular acceleration expression, carrying out recursion by adopting a recursion method to obtain the state quantity of the balance car at each preset moment and the second state quantity.
6. The method for controlling the balance car according to claim 5, wherein the obtaining the state quantity of the balance car and the second state quantity at each preset time by recursion according to the acceleration expression and the angular acceleration expression comprises:
determining a velocity expression of the balance car and an angular velocity expression of the inverted pendulum according to the acceleration expression and the angular acceleration expression;
determining a position expression of the balance vehicle and a swing angle expression of the inverted pendulum according to the speed expression and the angular velocity expression;
and sequentially recursion by adopting a recursion method according to the speed expression, the angular speed expression, the position expression and the swing angle expression to obtain the state quantity of the balance car at each preset moment and the second state quantity.
7. A control device of a balance car, characterized by comprising:
the first acquisition unit is used for acquiring a first state quantity of the balance car at the current moment;
a first determination unit, configured to predict a second state quantity of the balance car at a target time by using a model predictive control algorithm based on the first state quantity and a dynamic model of the balance car, and determine an error between the second state quantity and an expected state quantity of the balance car at the target time; the second state quantity is related to the first state quantity, thrust borne by the balance car at each control moment and the error, and the related relation forms a preset constraint condition, wherein the control moments comprise the current moment and a plurality of preset moments between the current moment and the target moment;
the second determining unit is used for determining the target thrust borne by the balance car at each control moment when the absolute value of the error is minimum under the condition that the preset constraint condition is met;
and the driving control unit is used for driving and controlling the balance car based on the target thrust borne by the balance car at the current moment.
8. A control device for a balance vehicle, comprising a processor, a memory, and a computer program stored in the memory and executable on the processor, wherein the processor executes the computer program to implement the control method for a balance vehicle according to any one of claims 1 to 7.
9. A balance car characterized by comprising the control device of the balance car according to claim 7 or 8.
10. A computer-readable storage medium storing a computer program, wherein the computer program, when executed by a processor, implements the control method of a balance car according to any one of claims 1 to 7.
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