CN114800517A - Multi-degree-of-freedom hydraulic mechanical arm real-time control system and method - Google Patents
Multi-degree-of-freedom hydraulic mechanical arm real-time control system and method Download PDFInfo
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- B—PERFORMING OPERATIONS; TRANSPORTING
- B25—HAND TOOLS; PORTABLE POWER-DRIVEN TOOLS; MANIPULATORS
- B25J—MANIPULATORS; CHAMBERS PROVIDED WITH MANIPULATION DEVICES
- B25J9/00—Programme-controlled manipulators
- B25J9/16—Programme controls
- B25J9/1602—Programme controls characterised by the control system, structure, architecture
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- B—PERFORMING OPERATIONS; TRANSPORTING
- B25—HAND TOOLS; PORTABLE POWER-DRIVEN TOOLS; MANIPULATORS
- B25J—MANIPULATORS; CHAMBERS PROVIDED WITH MANIPULATION DEVICES
- B25J18/00—Arms
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- B—PERFORMING OPERATIONS; TRANSPORTING
- B25—HAND TOOLS; PORTABLE POWER-DRIVEN TOOLS; MANIPULATORS
- B25J—MANIPULATORS; CHAMBERS PROVIDED WITH MANIPULATION DEVICES
- B25J19/00—Accessories fitted to manipulators, e.g. for monitoring, for viewing; Safety devices combined with or specially adapted for use in connection with manipulators
- B25J19/0054—Cooling means
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- B—PERFORMING OPERATIONS; TRANSPORTING
- B25—HAND TOOLS; PORTABLE POWER-DRIVEN TOOLS; MANIPULATORS
- B25J—MANIPULATORS; CHAMBERS PROVIDED WITH MANIPULATION DEVICES
- B25J9/00—Programme-controlled manipulators
- B25J9/16—Programme controls
- B25J9/1656—Programme controls characterised by programming, planning systems for manipulators
- B25J9/1664—Programme controls characterised by programming, planning systems for manipulators characterised by motion, path, trajectory planning
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- B—PERFORMING OPERATIONS; TRANSPORTING
- B25—HAND TOOLS; PORTABLE POWER-DRIVEN TOOLS; MANIPULATORS
- B25J—MANIPULATORS; CHAMBERS PROVIDED WITH MANIPULATION DEVICES
- B25J9/00—Programme-controlled manipulators
- B25J9/16—Programme controls
- B25J9/1679—Programme controls characterised by the tasks executed
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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
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- Y02P—CLIMATE CHANGE MITIGATION TECHNOLOGIES IN THE PRODUCTION OR PROCESSING OF GOODS
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- Y02P90/02—Total factory control, e.g. smart factories, flexible manufacturing systems [FMS] or integrated manufacturing systems [IMS]
Abstract
The invention belongs to the field of robot control, and provides a multi-degree-of-freedom hydraulic mechanical arm real-time control system and a multi-degree-of-freedom hydraulic mechanical arm real-time control method. The control system comprises a hydraulic mechanical arm module, an interaction unit and a control unit, wherein the hydraulic mechanical arm module comprises an encoder which is arranged at each joint of a freedom degree hydraulic driving mechanical arm body, and the encoder is used for acquiring a real-time angle of each joint; the interaction unit is used for realizing data transmission and interaction with the control unit; the control unit is used for obtaining the angle of the joint to be tracked by adopting an inverse solution method based on the real-time angle of each joint acquired by the hydraulic mechanical arm module according to a preset pose instruction so as to control the movement of the hydraulic mechanical arm; the encoder feeds back the angle in real time, so that the control unit obtains the current pose state of the hydraulic mechanical arm by adopting a forward solution algorithm based on the feedback angle. The invention ensures the reliable and high real-time movement of the hydraulic mechanical arm and is convenient for installation, maintenance and the like.
Description
Technical Field
The invention belongs to the field of robot control, and particularly relates to a multi-degree-of-freedom hydraulic mechanical arm real-time control system and method.
Background
The statements in this section merely provide background information related to the present disclosure and may not necessarily constitute prior art.
With the development of robotics, robots have been widely used in the fields of industry, agriculture, home, service, medical care, military, and the like. Common robot drive systems are primarily motor driven. The motor drive has the advantages of low noise, high precision and the like, but for a large load, the motor drive needs to be bulky. Compared with a motor driving system, the hydraulic driving mechanical arm system has the characteristics of higher load capacity, high-speed operation and the like under the condition of adopting relatively smaller volume and mechanism, and is widely applied to occasions of heavy load, underwater, special operation and the like. Such as fire rescue, strong magnetic field interference environment, petrochemical explosion environment, etc. The existing industrial mechanical arm is uniform in style, has a set of mature system framework and a control system, the hydraulic mechanical arm has a flexible design structure, a piston type hydraulic cylinder is mostly adopted as a driving unit to push a connecting rod of the mechanical arm to rotate, and the problems of retardation, crawling and the like are solved.
Disclosure of Invention
The invention provides a multi-degree-of-freedom hydraulic mechanical arm real-time control system and a multi-degree-of-freedom hydraulic mechanical arm real-time control method for solving the problems.
According to some embodiments, the invention adopts the following technical scheme:
in a first aspect, the invention provides a multi-degree-of-freedom hydraulic mechanical arm real-time control system.
A multi-degree-of-freedom hydraulic mechanical arm real-time control system comprises: the system comprises a hydraulic mechanical arm module, an interaction unit and a control unit, wherein the hydraulic mechanical arm module comprises an encoder which is arranged at each joint of a freedom degree hydraulic driving mechanical arm body, and the encoder is used for obtaining a real-time angle of each joint;
the interaction unit is used for realizing data transmission and interaction with the control unit;
the control unit is used for obtaining the angle of the joint to be tracked by adopting an inverse solution method based on the real-time angle of each joint acquired by the hydraulic mechanical arm module according to a preset pose instruction so as to control the movement of the hydraulic mechanical arm; the encoder feeds back the angle in real time, so that the control unit obtains the current pose state of the hydraulic mechanical arm by adopting a forward solution algorithm based on the feedback angle.
Furthermore, the hydraulic mechanical arm module is controlled by a hydraulic servo control system, the hydraulic servo control system comprises a hydraulic heat dissipation circulating system and a hydraulic servo driving system, and the hydraulic servo driving system comprises a hydraulic mechanical arm system.
Further, the hydraulic servo driving system is used for solving an expected angle according to an inverse solution method, obtaining an actual angle according to a high-gain differentiator, solving a position compensation voltage of an expected hydraulic servo valve by taking a difference value of the expected angle and the actual angle as an input quantity of the controller, and controlling the movement of the hydraulic mechanical arm system according to the position compensation voltage.
Further, the controller comprises a high-gain differentiator, a PID module and an RBF neural network module, wherein the high-gain differentiator is used for obtaining the speed of each joint according to the real-time angle of each joint acquired by the encoder.
Further, the position compensation voltage is:
u＝u p +y j +εsign(s)+ks，ε>0,k>0
wherein the content of the first and second substances,
y j is an estimated compensation term for the RBF neural network, and epsilon sign(s) + ks is a robust sliding-mode term, where
Is the filtered tracking error, e ═ θ d - θ is the tracking error.
Further, the estimated compensation term y of the RBF neural network j Comprises the following steps:
where ω is the weight of the output layer, h is the number of nodes of the hidden layer, n is the number of samples of the output, and y is the output of the neural network.
Further, the inverse solution comprises: when iteration starts, Levenberg-Marquardt is used as an initial iteration method, and when the initial iteration method is smaller than a residual display drop threshold, the method is switched to a quasi-Newton method to achieve second-order rapid convergence of the algorithm.
Further, the obtaining of the current pose state of the hydraulic mechanical arm by using a forward solution algorithm specifically includes: and solving a transformation matrix of the tail end connecting rod coordinate system relative to the base coordinate system by adopting the homogeneous coordinate transformation matrix of the connecting rod, and obtaining the current pose state of the hydraulic mechanical arm according to the transformation matrix of the tail end connecting rod coordinate system relative to the base coordinate system.
Furthermore, the hydraulic mechanical arm module further comprises a six-degree-of-freedom hydraulic driving mechanical arm body, an electro-hydraulic servo valve and a hydraulic cylinder, wherein the electro-hydraulic servo valve controls the hydraulic oil flow of the hydraulic cylinder to push the connecting rod to move.
In a second aspect, the invention provides a real-time control method for a multi-degree-of-freedom hydraulic mechanical arm.
A multi-degree-of-freedom hydraulic mechanical arm real-time control method adopts the multi-degree-of-freedom hydraulic mechanical arm real-time control system in the first aspect, and comprises the following steps:
determining an expected pose instruction;
obtaining the actual angle of the joint to be tracked by adopting an inverse solution method;
controlling a hydraulic servo driver to realize tracking according to the actual angle and the expected angle to obtain position compensation voltage; the hydraulic mechanical arm is used for controlling the hydraulic mechanical arm;
and feeding back the real-time angle of the joint by the encoder, and obtaining the current pose state of the hydraulic mechanical arm by adopting a forward solution algorithm.
Compared with the prior art, the invention has the beneficial effects that:
1. compared with the traditional PID control, the robust PID control strategy based on the error compensation has better robustness and tracking accuracy.
2. Aiming at solving the problem of complex solution of the inverse kinematics analytic solution of the multi-axis robot, the invention designs the iterative inverse kinematics solution algorithm based on the fusion of LM and quasi-Newton, and has high universality.
3. The invention builds a real-time motion control system based on motion control programming software CODESYS, adopts a multi-axis motion control scheme of 'virtual driving and real', can obtain better motion planning, and realizes position tracking.
4. The invention adopts real-time EtherCAT bus communication to establish the communication between the manipulator controller and the hydraulic manipulator slave station, thereby ensuring high synchronization precision, low time delay, high communication rate and the like of the manipulator system.
Drawings
The accompanying drawings, which are incorporated in and constitute a part of this specification, are included to provide a further understanding of the invention, and are incorporated in and constitute a part of this specification, illustrate exemplary embodiments of the invention and together with the description serve to explain the invention and not to limit the invention.
FIG. 1 is an overall architecture diagram of a multi-degree-of-freedom hydraulic manipulator real-time control system shown in an embodiment of the invention;
FIG. 2 is a flow chart of a multi-degree-of-freedom hydraulic robotic arm real-time control system shown in an embodiment of the present invention;
fig. 3 is an overall architecture diagram of a hydraulic servo control system shown in the embodiment of the present invention;
FIG. 4 is a flow chart illustrating a hydraulic servo drive system error compensation process in an embodiment of the present invention;
FIG. 5 is a flow chart of a joint inverse kinematics solution method shown in an embodiment of the present invention;
fig. 6 is a flowchart of a "virtual-drive-real" multi-axis motion control scheme shown in an embodiment of the present invention.
Detailed Description
The invention is further described with reference to the following figures and examples.
It should be noted that the following detailed description is exemplary and is intended to provide further explanation of the invention. Unless defined otherwise, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this invention belongs.
It is noted that the terminology used herein is for the purpose of describing particular embodiments only and is not intended to be limiting of exemplary embodiments according to the invention. As used herein, the singular is intended to include the plural unless the context clearly dictates otherwise, and it should be understood that when the term "comprising" is used in this specification it indicates the presence of the feature, step, operation, device, component and/or combination thereof.
In the present invention, terms such as "connected" and the like are to be understood in a broad sense and mean either fixedly connected or integrally connected or detachably connected; may be directly connected or indirectly connected through an intermediate. The specific meanings of the above terms in the present invention can be determined according to specific situations by persons skilled in the relevant scientific or technical field, and are not to be construed as limiting the present invention.
Example one
The embodiment provides a multi-degree-of-freedom hydraulic mechanical arm real-time control system.
A multi-degree-of-freedom hydraulic mechanical arm real-time control system comprises: the system comprises a hydraulic mechanical arm module, an interaction unit and a control unit, wherein the hydraulic mechanical arm module comprises an encoder which is arranged at each joint of a freedom degree hydraulic driving mechanical arm body, and the encoder is used for obtaining a real-time angle of each joint;
the interaction unit is used for realizing data transmission and interaction with the control unit;
the control unit is used for obtaining the angle of the joint to be tracked by adopting an inverse solution method based on the real-time angle of each joint acquired by the hydraulic mechanical arm module according to a preset pose instruction so as to control the movement of the hydraulic mechanical arm; the encoder feeds back the angle in real time, so that the control unit obtains the current pose state of the hydraulic mechanical arm by adopting a forward solution algorithm based on the feedback angle.
The multi-degree-of-freedom hydraulic mechanical arm real-time control system in the embodiment is shown in fig. 1 and comprises a hydraulic mechanical arm module, an interaction unit and a control unit, wherein the integral control system realizes data interaction and transmission between an upper computer and an actuator through a switch relay and by adopting a standard network port.
The hydraulic mechanical arm module comprises a six-degree-of-freedom hydraulic driving mechanical arm body, an electro-hydraulic servo valve, a piston cylinder, a swing cylinder and an absolute value encoder. The hydraulic mechanical arm body is a serial six-degree-of-freedom mechanical arm formed by six connecting rods in a serial hinged mode, and the connecting rods are driven to move by controlling the hydraulic oil flow of a hydraulic cylinder (a piston cylinder/a swing cylinder) through an electro-hydraulic servo valve. A high-precision absolute value encoder is installed at each joint to obtain current real-time angular position information of each joint in real time, thereby calculating the latest state of the robot.
The input of an electro-hydraulic servo valve control instruction of the hydraulic mechanical arm and the reading of feedback data of a numerical value of an encoder are realized by slave station equipment of a real-time hydraulic servo drive system based on EtherCAT. The hydraulic drive system is a slave station drive module of a special hydraulic servo valve amplifier designed and developed based on SMT32 and LAN9252I/ML slave station protocol chips, the time period can reach microsecond level, and the real-time performance of mechanical arm system communication is guaranteed.
The interaction unit is a module for interaction between the mechanical arm and the external environment, so that the external environment is sensed, and then the hydraulic mechanical arm is driven to complete corresponding actions.
The control unit is a control center part of the whole system and is used for completing the motion control generation of the mechanical arm and the issuing of a control command; processing and transmitting data of the information uploaded by the interaction unit; and data conversion and transmission between the upper computer, the teleoperator and the mechanical arm.
Specifically, as shown in fig. 2, a hydraulic manipulator control method includes inputting an expected pose instruction, solving joint angle information to be tracked through an inverse solution method, enabling joint angles to be tracked through a proposed hydraulic servo control system, enabling an encoder to feed back real-time state information to be provided for a controller and achieve feedback control, and solving the tail end state of a manipulator through a forward solution algorithm to achieve real-time state monitoring of an upper computer.
The hydraulic servo control system includes a hydraulic heat dissipation system and a hydraulic servo drive system, as shown in fig. 3.
(a) Hydraulic heat dissipation circulating system
The hydraulic heat dissipation circulation system adopts an independent gear pump active circulation air cooling type cooling scheme. Compared with an overflow valve oil return cooling method, the cooling efficiency is higher. The heat dissipation system meets the heat dissipation requirement through the test of heat production power and a temperature rise curve, the temperature requirement, the existing parameters and the like. The calculation mode of the cooler is that the hydraulic mechanical arm is started, the temperature rise (delta T) curve of the temperature of the hydraulic oil from room temperature to the set allowable temperature is measured for multiple times, and according to the parameters of the existing hydraulic station: the oil tank capacity V, the hydraulic oil heat capacity c and the hydraulic oil density rho are calculated to generate heat power:
P v ＝ΔT·c·ρ·V/t/60 (1)
calculating the power of the cooling system:
P s ＝P v ·η/ΔT (2)
wherein eta is a safety factor. The size of the final cooler can be obtained, and 30% -50% of redundant design is carried out on the size of the cooler to prepare for designing an oil temperature control system.
The oil temperature heat dissipation control system is designed as follows:
firstly, the temperature of hydraulic oil is obtained through a special temperature sensor for the hydraulic oil, and an upper and a lower bounds of the oil temperature, such as [ a, b ], are preset. When the oil temperature reaches the set maximum value b, the radiating system is started, and when the oil temperature is reduced to the set minimum value a, the radiating system is closed, so that the continuous operation of heat radiation is avoided, and the consumption of electric quantity is saved.
(b) Hydraulic servo driving system
Because the problems of parameter perturbation, external interference, nonlinear friction force and the like exist in a hydraulic servo position driving system, the traditional PID-based driving mode easily generates phenomena of hysteresis and the like, and a position error compensation controller formed by combining a slip film control (SMC) and a Radial Basis Function (RBF) neural network on the basis of the traditional PID control is designed. The control flow chart is shown in fig. 4.
The control flow of the hydraulic servo driving system is as follows: and solving the control current value u of the expected hydraulic servo valve by using the difference value between the expected angle and angular velocity value and the actual angle and angular velocity solved by the high-gain differentiator as the input quantity of the controller through an inverse solution. The encoder acquires the pulse value of the joint encoder in real time and converts the pulse value into an angle value of a corresponding joint through an algorithm, and the high-gain differentiator (3) is used for solving the speed value of the joint encoder according to the angle value.
The high-gain differentiator is:
wherein x is 1 Is the actual joint angle value theta of the robot obtained by the encoder,
and
estimating the differential of the state, k, for the robot, respectively 1 、κ 2 And kappa 3 Are positive and satisfy the constant coefficient parameters of Hurwitz.
Is a small constant.
The PID control signals are:
wherein, theta d And theta is the desired and actual joint angle values, respectively. K p 、K I And K D Three control parameters of the PID controller are respectively.
The activation function of the RBF neural network is:
where c is the center vector and σ is the width of the gaussian basis function.
The output of the network is:
where ω is the weight of the output layer, h is the number of nodes of the hidden layer, n is the number of samples of the output, and y is the output of the neural network.
The final position compensation output is:
u＝u p +y j +εsign(s)+ks，ε>0,k>0 (7)
wherein, y j Is an estimated compensation term for the RBF neural network, and ε sign(s) + ksis a robust sliding-mode term, where
Is the filtered tracking error, e ═ θ d - θ is the tracking error. u is the control command of the actual hydraulic servo.
And controlling the hydraulic servo position system by adopting a robust PID and neural network fusion control method, wherein u is a current value for the hydraulic servo valve.
In the embodiment, a hydraulic manipulator control unit system is constructed based on a real-time industrial Ethernet field bus EtherCAT and an open software platform CODETYS 3.5, and a hydraulic manipulator real-time motion controller based on a Windows platform is designed, wherein the CODETYS is a complete development environment of a programmable logic control PLC and runs in an industrial personal computer of a Windows platform provided with a real-time operating environment (RTE). The control unit comprises a positive and negative kinematics model and solution algorithm of the hydraulic mechanical arm, a mechanical arm track tracking algorithm, a visual interface and the like. And the accurate real-time motion control of the robot is realized by sending and receiving data commands in real time through an EtherCAT bus.
The specific content of the motion control unit comprises:
(1) positive kinematics
The present embodiment completes the kinematics modeling of the mechanical arm system by using a common DH method. The positive kinematics adopts a homogeneous coordinate transformation matrix (8) of the connecting rod to solve,
wherein, a i-1 ，α i-1 ，d i And theta i Is a DH parameter by transforming the matrix of each link
The sequential multiplication yields a transformation matrix of the end link coordinate system { n } relative to the base coordinate system {0 }:
wherein q is i Is the angle value of the ith joint, R is the rotation matrix and P is the current end position.
Through the calculation, the current pose state (x, Y, z, R, P, Y) of the mechanical arm can be obtained according to the feedback data of the mechanical arm, wherein x, Y and z are position information of the tail end of the mechanical arm under a base coordinate system. R, P and Y are attitude information of the tail end of the mechanical arm under the base coordinate system.
(2) Inverse kinematics of robot
The embodiment provides a Levenberg-Marquardt and quasi-Newton combined inverse kinematics solving method, rapid convergence can be achieved under the condition of large deviation based on a Levenberg-Marquardt iteration method, global secondary convergence can be tried under the condition of small deviation by a quasi-Newton method, and the combined robot inverse kinematics solving method is designed by combining the characteristics of the Levenberg-Marquardt and the quasi-Newton. The specific process comprises the following steps: when iteration starts, Levenberg-Marquardt is used as an initial iteration method, and when the requirement of residual display drop is met, the method is switched to a quasi-Newton method to achieve second-order rapid convergence of the algorithm.
By the principle of the gradient descent method, solving the inverse kinematics optimal solution can be summarized as searching the local minimum problem of the next state according to the current state, namely, the solution can be expressed as follows: x is the number of k+1 ＝x k + α h, wherein x k And x k+1 Respectively representing the current state, h is the search direction, alpha is the step length, and finally the problem of finding the optimal search direction and step length is solved.
The Levenberg-Marquardt (LM, Levenberg-Marquardt) algorithm is a method for increasing a confidence interval to belong to a confidence domain on the basis of Gauss Newton, and the method is characterized in that the confidence interval belongs to the confidence domain through an iterative step formula: (J) T J+λI)h＝J T f,λ>0, finding the search direction h. Wherein (J) T J + λ I) is an approximation of the hessian matrix, J is the jacobian matrix of the robotic system, f is the residual, i.e., the difference between the actual observed and estimated values, λ is an incremental penalty factor, and the improved update strategy of Nielsen, 1999, is adopted:
wherein the content of the first and second substances,
is the gain ratio, the denominator is the descent of the approximation model, and the numerator is the descent of the actual model. F (x) -F (x + h) is the difference value of adjacent steps of the expectation minimization function, L (h) is the estimated value of F (x + h), L (0) is the initial value of the estimated value, upsilon is a factor, and the initial value is 2.
The quasi-Newton method adopts a BFGS algorithm to approximate the Hessian matrix, and the approximate update rate is as follows:
wherein x is d The expected pose value of the user, x is the actual pose value of the system,
the difference between the expected value and the actual value. y is the difference in gradient between adjacent steps, g k+1 And g k The gradient of the adjacent steps is respectively, B is an iterative formula of a BFGS algorithm, and h is a search direction.
Wherein the determination condition is | f' (x) & gtY ∞ <0.02f (x), that is, when the difference is small, the LM method is converted into the quasi-Newton method. Finally, there is a current value x k By iterative formula x with search direction k+1 ＝x k The optimal angle x of the next iteration can be obtained by + alpha h k+1 。
Based on the above principle, the inverse kinematics calculation block diagram is shown in fig. 5.
In this embodiment, a "virtual-drive-real" multi-axis motion control scheme is designed, specifically: the method comprises the steps of defining 6 virtual axes in CODESYS software, firstly controlling the defined virtual axes by angles obtained by robot kinematics, interpolating the virtual axes into expected virtual tracking tracks by utilizing functions controlByPos and according to expected target position information and information such as expected maximum speed and maximum acceleration set by a user, and then sending the position information of the virtual axes to a hydraulic drive controller to drive a mechanical arm to realize real-time motion control. The scheme of the multi-axis motion control of "virtual driving and real" is shown in fig. 6, where the part in the dashed box is a virtual position generator, and where ControlByPos is a function block for controlling fixed-point motion according to position information.
The real-time control system comprises a multi-degree-of-freedom hydraulic driving mechanical arm body, a hydraulic driving unit, a data acquisition unit, a mechanical arm control unit, an interaction unit, a data bus and the like. The mechanical arm body adopts a self-designed Ethercat-based servo amplifier to send a current value to an electro-hydraulic servo valve from a station module so as to push a hydraulic cylinder to realize telescopic motion; the current value is obtained by calculating in real time by a motion control algorithm from data given by a user and fed back by the mechanical arm data acquisition unit by the control unit. The data acquisition unit is composed of an encoder arranged at each joint, and a real-time joint motion position feedback loop is formed by acquiring and feeding back the numerical value of the encoder; in parallel with the mechanical arm there are also interaction units, such as six-dimensional force sensors, cameras, lasers, etc. All devices adopt the combination of Ethercat and TCP/IP to realize communication and data exchange. The control unit comprises a control software system which runs on the industrial personal computer and is developed based on an Ethercat bus, and a human-computer interaction interface based on TCP/IP, so that data communication between the control unit and the interaction unit is realized. The interaction unit may be a six-dimensional force sensor, a camera, or the like. All the devices realize communication and data exchange through the intermediate switch.
A multi-degree-of-freedom hydraulic mechanical arm control method is designed, and comprises a mechanical arm forward and backward kinematics algorithm and a hydraulic servo control method, wherein the method is operated in an industrial personal computer provided with a real-time system RTE in figure 1. Aiming at the problem that the analytical solution of the mechanical arm kinematics inverse solution is difficult to solve, an iterative mechanical arm inverse solution solving algorithm is provided. And a robust tracking control algorithm based on SMC and RBF is designed to realize the tracking of the expected angle.
The embodiment designs a hydraulic mechanical arm control system and a control method based on an industrial PC (personal computer) from two aspects of hardware and software based on the ideas of openness, modularization and bus. The hydraulic mechanical arm has compact and simple integral structure and universality, ensures reliable motion and high real-time performance of the hydraulic mechanical arm, and is convenient to install, maintain and the like.
Example two
The embodiment provides a real-time control method for a multi-degree-of-freedom hydraulic mechanical arm.
A multi-degree-of-freedom hydraulic mechanical arm real-time control method adopts a multi-degree-of-freedom hydraulic mechanical arm real-time control system in the embodiment I, and comprises the following steps:
determining an expected pose instruction;
obtaining the actual angle of the joint to be tracked by adopting an inverse solution method;
controlling a hydraulic servo driver to realize tracking according to the actual angle and the expected angle to obtain position compensation voltage; the hydraulic mechanical arm is used for controlling the hydraulic mechanical arm;
and feeding back the real-time angle of the joint by the encoder, and obtaining the current pose state of the hydraulic mechanical arm by adopting a forward solution algorithm.
The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention, and various modifications and changes may be made by those skilled in the art. Any modification, equivalent replacement, or improvement made within the spirit and principle of the present invention should be included in the protection scope of the present invention.
Claims (10)
1. The utility model provides a multi freedom hydraulic mechanical arm real-time control system which characterized in that includes: the system comprises a hydraulic mechanical arm module, an interaction unit and a control unit, wherein the hydraulic mechanical arm module comprises an encoder which is arranged at each joint of a freedom degree hydraulic driving mechanical arm body, and the encoder is used for obtaining a real-time angle of each joint;
the interaction unit is used for realizing data transmission and interaction with the control unit;
the control unit is used for obtaining the angle of the joint to be tracked by adopting an inverse solution method based on the real-time angle of each joint acquired by the hydraulic mechanical arm module according to a preset pose instruction so as to control the movement of the hydraulic mechanical arm; the encoder feeds back the angle in real time, so that the control unit obtains the current pose state of the hydraulic mechanical arm by adopting a forward solution algorithm based on the feedback angle.
2. The multi-degree-of-freedom hydraulic mechanical arm real-time control system as claimed in claim 1, wherein the hydraulic mechanical arm module is controlled by a hydraulic servo control system, the hydraulic servo control system comprises a hydraulic heat dissipation circulation system and a hydraulic servo drive system, and the hydraulic servo drive system comprises a hydraulic mechanical arm system.
3. The multi-degree-of-freedom hydraulic mechanical arm real-time control system according to claim 2, wherein the hydraulic servo drive system is configured to solve the expected angle according to an inverse solution method, obtain the actual angle according to a high-gain differentiator, use a difference between the expected angle and the actual angle as an input of the controller, solve the position compensation voltage of the expected hydraulic servo valve, and control the movement of the hydraulic mechanical arm system according to the position compensation voltage.
4. The multi-degree-of-freedom hydraulic mechanical arm real-time control system according to claim 3, wherein the controller comprises a high-gain differentiator, a PID module and an RBF neural network module, and the high-gain differentiator is used for obtaining the speed of each joint according to the real-time angle of each joint obtained by the encoder.
5. The multi-degree-of-freedom hydraulic mechanical arm real-time control system according to claim 3, wherein the position compensation voltage is:
u＝u p +y j +εsign(s)+ks，ε>0,k>0
wherein the content of the first and second substances,
y j is an estimated compensation term for the RBF neural network, and epsilon sign(s) + ks is a robust sliding-mode term, where
Is the filtered tracking error, e ═ θ d - θ is the tracking error.
6. The system as claimed in claim 5, wherein the estimated compensation term y of the RBF neural network is the same as the estimated compensation term y of the MDF hydraulic mechanical arm j Comprises the following steps:
where ω is the weight of the output layer, h is the number of nodes of the hidden layer, n is the number of samples of the output, and y is the output of the neural network.
7. The real-time control system of the multi-degree-of-freedom hydraulic mechanical arm according to claim 1, wherein the inverse solution comprises: when iteration starts, Levenberg-Marquardt is used as an initial iteration method, and when the initial iteration method is smaller than a residual display drop threshold, the method is switched to a quasi-Newton method to achieve second-order rapid convergence of the algorithm.
8. The system for controlling the multi-degree-of-freedom hydraulic mechanical arm in real time according to claim 1, wherein the obtaining of the current pose state of the hydraulic mechanical arm by using a forward solution algorithm specifically comprises: and solving a transformation matrix of the tail end connecting rod coordinate system relative to the base coordinate system by adopting the homogeneous coordinate transformation matrix of the connecting rod, and obtaining the current pose state of the hydraulic mechanical arm according to the transformation matrix of the tail end connecting rod coordinate system relative to the base coordinate system.
9. The real-time control system of the multi-degree-of-freedom hydraulic mechanical arm of claim 1, wherein the hydraulic mechanical arm module further comprises a six-degree-of-freedom hydraulic driving mechanical arm body, an electro-hydraulic servo valve and a hydraulic cylinder, and the electro-hydraulic servo valve controls hydraulic oil flow of the hydraulic cylinder to push the connecting rod to move.
10. A multi-degree-of-freedom hydraulic mechanical arm real-time control method, which is characterized in that the multi-degree-of-freedom hydraulic mechanical arm real-time control system of any one of claims 1 to 9 is adopted, and comprises the following steps:
determining an expected pose instruction;
obtaining the actual angle of the joint to be tracked by adopting an inverse solution method;
controlling a hydraulic servo driver to realize tracking according to the actual angle and the expected angle to obtain position compensation voltage; the hydraulic mechanical arm is used for controlling the hydraulic mechanical arm;
and feeding back the real-time angle of the joint by the encoder, and obtaining the current pose state of the hydraulic mechanical arm by adopting a forward solution algorithm.
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