Teleoperation robot control method based on event triggering and finite time control

Abstract

The invention relates to a teleoperation robot control method based on event triggering and finite time control, which solves the problem of poor stability of asymmetric variable delay of a teleoperation robot, realizes finite time position tracking convergence and saves network communication resources. The method comprises the steps that a master end position signal and a slave end position signal passing through a zero-order retainer are sent into a master end finite time controller to calculate control torque, and the control torque is sent to a master end robot to control the motion of the master end robot; the main end position signal is sent into a main end event triggering decision maker, and whether the current main end position information is transmitted through a communication network is judged based on a main end event triggering strategy; a slave end position signal and a master end position signal passing through the zero-order retainer are sent to a slave end finite time controller to calculate a control moment, and the control moment is sent to a slave end robot to control the slave end robot to move; a slave end robot position signal is sent to a slave end event triggering decision maker, and whether the communication network is used for transmitting current slave end position information or not is judged based on a slave end event triggering strategy.

Description

Technical Field

[0001] The invention relates to the technical field of control of a teleoperated robot, and in particular to a teleoperated robot control method based on event triggering and limited time control. Background Art

[0002] Teleoperated robots are a typical human-machine environment interaction system, where operators can combine the robot's high precision and consistency performance to complete many complex tasks. In many engineering applications, robots have been able to help or even replace humans in performing tasks in many application scenarios. However, in some ever-changing, complex and dangerous work scenarios, it is still necessary to use remote operation systems to enable operators to remotely perform task operations. At present, remote robot systems have been applied in many engineering fields, such as aerospace, deep-sea exploration, medical surgery, industrial operations, and detection and operation in dangerous environments.

[0003] A teleoperation system can be considered as an interconnection between two parts through communication: the master robot and the master controller, and the slave robot and the slave controller. The operator applies force to the master robot to make it move, and the slave robot contacts the environment and completes the task. Bilateral control is an important control architecture for teleoperated robots. For bilateral teleoperated robot systems, the master controller and the slave controller need to transmit status information to each other through the communication channel. Position tracking performance is an important evaluation criterion that can be compiled to determine whether the slave robot can quickly and accurately reflect the operator's purpose, and whether the master robot can feedback the slave robot's operation to the operator.

[0004] The transmission delay problem in the communication channel of the teleoperated robot needs to be solved to ensure the stability and position tracking performance of the closed-loop teleoperated robot system. On the one hand, the inevitable communication delay will reduce the stability of the closed-loop system, and asymmetric delay will even cause the position tracking of the master and slave robots to be out of sync. On the other hand, data is packaged and exchanged in the communication network. The data transmission process is discontinuous, involving packet loss, data congestion, etc. Once a communication failure occurs, it will weaken the control performance of the teleoperated robot system and even make the system unstable. Summary of the invention

[0005] The purpose of the present invention is to provide a remote-controlled robot control method based on event triggering and finite-time control, so as to solve the problem of poor stability of asymmetric time-varying delays in bilateral remote-controlled robot systems, achieve finite-time position tracking convergence, further simplify the controller structure, and save data network communication resources.

[0006] In order to achieve the above object, the present invention provides a remote-controlled robot control method based on event triggering and limited time control, and the specific technical scheme is as follows:

[0007] A teleoperated robot control method based on event-triggered communication and limited time control comprises the following steps:

[0008] On the master robot side:

[0009] The communication network obtains the slave position information uploaded to the communication network by the slave event trigger, and sends the position information to the zero-order holder; if the slave event trigger does not upload the slave position information to the communication network, it means that no data transmission occurs in the communication network at this time, and no new slave robot position signal is sent to the zero-order holder;

[0010] The position information of the slave robot and the master robot output by the zero-order holder are sent to the master finite time controller to calculate the control torque acting on the master robot;

[0011] The master robot moves under the control torque calculated by the master controller to obtain the position information of the master robot;

[0012] The position information of the master robot is sent to the master event trigger, and the master event trigger strategy in the master event trigger determines whether to send the current position information of the master robot to the communication network for transmission to the slave;

[0013] And / or, on the slave robot side:

[0014] The communication network obtains the master-end position information uploaded to the communication network by the master-end event trigger, and sends the position information to the zero-order holder; if the master-end event trigger does not upload the master-end position information to the communication network, it means that no data transmission occurs in the communication network at this time, and no new master-end robot position signal is sent to the zero-order holder;

[0015] The position information of the master robot and the slave robot output by the zero-order holder are sent to the slave-end time-limited controller to calculate the control torque acting on the slave robot;

[0016] The slave robot moves under the control torque calculated by the slave controller to obtain the position information of the slave robot;

[0017] The position information of the slave robot is sent to the slave event trigger, and the slave event trigger strategy in the slave event trigger determines whether to send the current position information of the slave robot to the communication network for transmission to the master.

[0018] The beneficial effects of the present invention are:

[0019] On the one hand, the designed controller combines proportional terms, damping terms and adaptive methods. Compared with the existing related control methods, the designed controller has a simple structure, small gain and is easy to implement in practice. On the other hand, the designed controller contains a new event-triggered communication strategy containing non-integer power terms to ensure that the synchronization error converges within a limited time. It has been verified that the control method of the present invention can achieve stable position synchronization control of the master-slave robot and has faster position convergence performance. At the same time, the amount of data transmitted in the communication channel is also reduced, saving the amount of data transmitted in the communication network. BRIEF DESCRIPTION OF THE DRAWINGS

[0020] The drawings that constitute part of the present invention are used to assist in the description of the present invention. The contents provided in the drawings and their related descriptions in the present invention can be used to explain the present invention, but do not constitute improper limitations on the present invention. In the drawings:

[0021] Figure 1 The present invention is a schematic diagram of a teleoperated robot control method based on event-triggered communication and limited time control according to an embodiment of the present invention. DETAILED DESCRIPTION

[0022] The technical solution of the present invention will be described clearly and completely below in conjunction with the accompanying drawings in the embodiments of the present invention. A person skilled in the art will be able to implement the present invention based on these descriptions.

[0023] In addition, the embodiments of the present invention involved in the following description are generally only a part of the embodiments of the present invention, rather than all the embodiments. Therefore, based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work should fall within the scope of protection of the present invention.

[0024] like Figure 1 As shown, the bilateral teleoperated robot system with time-varying delay in this embodiment is a nonlinear time-varying system, which can be described as

[0025] The model expression of the master robot is:

[0026]

[0027] The model expression of the slave robot is:

[0028]

[0029] Among them, the subscript m represents the master robot, the subscript s represents the slave robot, and q m is the joint position of the master robot, is the joint velocity of the master robot, The joint acceleration of the master robot, q s is the joint position of the slave robot, is the joint velocity of the slave robot, is the joint acceleration of the slave robot, M m (q m ), M s (q s )∈R(n×n) are the symmetric positive definite inertia matrices of the master robot and the slave robot respectively, are the centrifugal force and Coriolis force of the master robot and the slave robot, respectively, G m (q m ), G s (q s )∈R n are the gravity terms of the master robot teleoperation system and the slave robot teleoperation system, respectively, and F m , F s ∈R n represent friction and external disturbance torque respectively, τ m , τ s ∈R n are the control torques of the master robot controller and the slave robot controller, τ h , τ e ∈R n They are the master-end force and the slave-end force respectively. The master-end force is the interaction force between the operator and the master-end robot, and the slave-end force is the interaction force between the slave-end robot and the environment. n represents the degree of freedom of the robot.

[0030] The above-mentioned teleoperated robot control method based on event-triggered communication and limited time control comprises the following steps:

[0031] (1) On the master robot side:

[0032] The communication network obtains the slave position information uploaded to the communication network by the slave event trigger, and sends the position information to the zero-order holder; if the slave event trigger does not upload the slave position information to the communication network, it means that no data transmission occurs in the communication network at this time, and no new slave robot position signal is sent to the zero-order holder;

[0033] Due to the zero-order holder, when the communication network has new slave robot position information, the zero-order holder outputs the new slave robot position information; when no new slave robot position signal is sent, the zero-order holder outputs the original slave robot position information;

[0034] The position information of the slave robot and the master robot output by the zero-order holder are sent to the master finite time controller to calculate the control torque acting on the master robot;

[0035] The master robot moves under the control torque calculated by the master controller to obtain the position information of the master robot;

[0036] The position information of the master robot is sent to the master event trigger, and the master event trigger strategy in the master event trigger determines whether to send the current position information of the master robot to the communication network for transmission to the slave;

[0037] (2) On the slave robot side:

[0038] The communication network obtains the master-end position information uploaded to the communication network by the master-end event trigger, and sends the position information to the zero-order holder; if the master-end event trigger does not upload the master-end position information to the communication network, it means that no data transmission occurs in the communication network at this time, and no new master-end robot position signal is sent to the zero-order holder;

[0039] Due to the zero-order holder, when the communication network has new master-end robot position information, the zero-order holder outputs the new master-end robot position information; when no new master-end robot position signal is sent, the zero-order holder outputs the original master-end robot position information;

[0040] The position information of the master robot and the slave robot output by the zero-order holder are sent to the slave-end time-limited controller to calculate the control torque acting on the slave robot;

[0041] The slave robot moves under the control torque calculated by the slave controller to obtain the position information of the slave robot;

[0042] The position information of the slave robot is sent to the slave event trigger, and the slave event trigger strategy in the slave event trigger determines whether to send the current position information of the slave robot to the communication network for transmission to the master.

[0043] Among them, the implementation process of the master robot finite time controller is described as follows:

[0044] The communication channel is sent to the master-end zero-order holder, and the output signal is

[0045] Combine the position signal and speed signal of the master robot to construct the auxiliary variable of the master robot controller as follows:

[0046]

[0047] Among them, λ is the auxiliary variable gain coefficient of the master robot controller.

[0048] The finite time controller of the master robot is:

[0049]

[0050] Where K represents the controller gain coefficient; α m represents the damping coefficient of the master controller, 0<σ<1 is the non-integer power of the master controller, κ m is the compensation term of the master robot controller, which is expressed as:

[0051]

[0052] Among them, G n (q m ) is the gravity moment compensation item of the master robot; Represents the RBF neural network adaptive term; represents the adaptive compensation term; is the gain weight coefficient matrix of the RBF neural network of the main robot, It is the Gaussian function vector of the RBF neural network of the master robot. It can be obtained by the following expression:

[0053]

[0054]

[0055] Among them, l represents the number of intermediate nodes of the main-end RBF neural network, x m is the input vector of the main RBF neural network, c mi is the center vector of the ith Gaussian function of the main RBF neural network, b m is the width of the Gaussian function.

[0056] They can be obtained through the following master controller learning law:

[0057]

[0058] Γ m1 , Γ m2 Learning law coefficient for the master controller.

[0059] The controller of the main robot can be divided into three parts: the first part is -Ksig(s m ) σ , which is mainly used for position error feedback control law to realize the position tracking of the slave robot by the master robot; the second part is The main function is the damping term, which is used to maintain the stability of the time-delay system; the third part is κ m , is the system compensation term, which is used to compensate for the robot's gravity torque, friction torque and external torque.

[0060] The introduction of non-integer powers in the control law ensures the finite-time performance of the system position control.

[0061] Whether the master position signal is sent to the communication network and transmitted to the slave robot is determined by the master event trigger.

[0062] The implementation process of the main-side robot event trigger is as follows:

[0063] The position signal output by the last master robot event trigger is expressed as Combined with the master robot position signal q currently sent to the master robot event trigger m , the master robot event trigger error e can be calculated mE (t) is

[0064]

[0065] When the master robot event triggers the error e mE (t) satisfies the following event triggering policy conditions, expressed as

[0066]

[0067] Then the master robot event trigger outputs signal q m and outputs the position signal to the communication network, which is then transmitted to the slave side.

[0068] For the above event triggering strategy, λ 12 ,λ 22 >0 is the main robot event trigger coefficient, is the master robot event trigger coefficient, which is expressed as

[0069]

[0070] Among them, k mE is the event trigger weight of the main robot, d m The upper bound of the communication delay from the master robot to the slave robot.

[0071] The implementation process of the slave robot finite time controller is described as follows:

[0072] The communication channel is sent to the slave zero-order holder, and the output signal is

[0073] Combine the position signal and velocity signal of the slave robot to construct the slave robot controller auxiliary variable of the following expression:

[0074]

[0075] Where λ is the auxiliary variable gain coefficient of the slave robot controller.

[0076] The finite time controller of the slave robot is:

[0077]

[0078] Where K represents the controller gain coefficient, which is the same as that in the master-side finite time controller; α s represents the damping coefficient of the master controller, 0<σ<1 is the non-integer power of the master controller, κ s is the compensation term of the master robot controller, which is expressed as:

[0079]

[0080] Among them, G s (q s ) is the gravity moment compensation item of the master robot; represents the adaptive term of the slave robot RBF neural network; represents the adaptive compensation item of the slave robot; is the gain weight coefficient matrix of the slave robot RBF neural network, is the Gaussian function vector of the slave robot RBF neural network. It can be obtained by the following formula:

[0081]

[0082]

[0083] Among them, l represents the number of intermediate nodes of the slave RBF neural network, x s is the input vector of the slave RBF neural network, c si is the center vector of the i-th Gaussian function of the slave RBF neural network, b s is the width of the Gaussian function of the slave controller.

[0084] They can be obtained by the following slave controller learning law:

[0085]

[0086] Γ s1 , Γ s2 Learning law coefficient for slave controller.

[0087] The controller of the slave robot can be divided into three parts: the first part is -Ksig(s s ) σ, which is mainly used for position error feedback control law to realize the position tracking of the master robot by the slave robot; the second part is The main function is the damping term, which is used to maintain the stability of the time-delay system; the third part is κ s , is the system compensation item, which is used to compensate for the gravity torque, friction torque and external torque of the slave robot.

[0088] The introduction of non-integer powers in the control law ensures the finite-time performance of the system position control.

[0089] Whether the master-end position signal is sent to the communication network and transmitted to the master-end robot is judged and determined by the slave-end event trigger.

[0090] The implementation process of the slave robot event trigger is as follows:

[0091] The position signal of the last output from the slave robot event trigger after passing through the zero-order holder is expressed as Combined with the master robot position signal qs currently sent to the master robot event trigger, the master robot event trigger error e is calculated sE (t) is

[0092]

[0093] When the master robot event triggers the error e sE (t) satisfies the following event triggering policy conditions, expressed as

[0094]

[0095] The slave robot event trigger outputs a signal qs, and outputs the position signal to the communication network for transmission to the master. For the above event trigger strategy, λ2, λ 22 >0 is the event trigger coefficient of the slave robot. is the event trigger coefficient of the slave robot, which is expressed as

[0096]

[0097] Among them, k sE is the event trigger weight of the slave robot, d s is the upper bound of the communication delay from the slave robot to the master robot.

[0098] The stability of the teleoperated robot system using the control method of the present invention is demonstrated and analyzed by using the Lyapunov function.

[0099] The Lyapunov-Krasovskii functional is chosen as:

[0100] V=V1+V2+V3+V4+V5

[0101]

[0102]

[0103]

[0104]

[0105]

[0106] Taking its derivative and substituting it into the control law and adaptive law of the master and slave robots, we can get

[0107] Considering the time trigger strategy in the event trigger, we can further get

[0108]

[0109] in

[0110]

[0111]

[0112]

[0113]

[0114]

[0115] Integrating the above inequality, we get

[0116]

[0117] Furthermore, we can get q m -q s 、e mE 、e sE , and Are all bounded.

[0118] Based on the error definition of event triggering, we can get

[0119]

[0120]

[0121] Therefore, we can further obtain and Are all bounded.

[0122] According to the dynamic model of the teleoperated robot system, we can get

[0123]

[0124] therefore, is bounded, using Barbarat's corollary, we have

[0125] Considering the event trigger error, its derivative is

[0126]

[0127] Using the definition of derivative, we have the following formula

[0128]

[0129] Further we can get

[0130]

[0131] Therefore, there is no condition for event triggering to be triggered infinitely.

[0132] Finally, based on the above analysis, the finite-time tracking performance of the system can be demonstrated.

[0133] The Lyapunov function is constructed as:

[0134]

[0135] in,

[0136] Substituting the control law and adaptive learning law, combined with the scaling relationship of the inequality, we can get

[0137]

[0138] in,

[0139]

[0140] Ξ=ξ m1 +ξ m2 +ξ s1 +ξ s2

[0141] Among them, ξ m1 , m2 , s1 and s2 are all positive numbers and satisfy

[0142]

[0143]

[0144]

[0145]

[0146] As a result, the position tracking of the closed-loop system has the characteristic of finite-time convergence.

[0147] It can be seen that the control method of this embodiment can effectively realize the position tracking control of the asymmetric time-varying and time-delay teleoperation robot system.

[0148] The above is a description of the relevant contents and implementation methods of the present invention. Without departing from the design concept of the present invention, ordinary technicians in this field can implement the present invention based on the above description. Based on the above content of the present invention, all other embodiments obtained by ordinary technicians in this field without making creative work should fall within the scope of protection of the present invention.

Claims

1. A teleoperated robot control method based on event triggering and limited time control, characterized in that: include: On the master robot side: The communication network obtains the slave position information uploaded to the communication network by the slave event trigger, and sends the position information to the zero-order holder; The position information of the slave robot and the master robot output by the zero-order holder are sent to the master finite time controller to calculate the control torque acting on the master robot; The master robot moves under the control torque calculated by the master finite time controller to obtain the position information of the master robot; The position information of the master robot is sent to the master event trigger, and the master event trigger strategy in the master event trigger determines whether to send the current position information of the master robot to the communication network for transmission to the slave; And / or, on the slave robot side: The communication network obtains the master end position information uploaded to the communication network by the master end event trigger, and sends the position information to the zero-order holder; The position information of the master robot and the slave robot output by the zero-order holder are sent to the slave finite time controller to calculate the control torque acting on the slave robot; The slave robot moves under the control torque calculated by the slave finite time controller to obtain the position information of the slave robot; The position information of the slave robot is sent to the slave event trigger, and the slave event trigger strategy in the slave event trigger determines whether to send the current position information of the slave robot to the communication network for transmission to the master.

2. The teleoperated robot control method based on event triggering and limited time control according to claim 1 is characterized in that: The model expression of the master robot is: The model expression of the slave robot is: Among them, the subscript m represents the master robot, the subscript s represents the slave robot, and q m is the joint position of the master robot, is the joint velocity of the master robot, The joint acceleration of the master robot, q s is the joint position of the slave robot, is the joint velocity of the slave robot, is the joint acceleration of the slave robot, M n (q m ), M s (q s )∈R(n×n) are the symmetric positive definite inertia matrices of the master robot and the slave robot respectively, are the centrifugal force and Coriolis force of the master robot and the slave robot, respectively, G m (q m ), G s (q s )∈R n are the gravity terms of the master robot teleoperation system and the slave robot teleoperation system, respectively, and F m , F s ∈R n represent friction and external disturbance torque respectively, τ m , τ s ∈R n are the control torques of the master robot controller and the slave robot controller, τ h , τ e ∈R n They are the master end force and the slave end force respectively. The master end force is the interaction force between the operator and the master end robot, and the slave end force is the interaction force between the slave end robot and the environment. n represents the degree of freedom of the robot.

3. The teleoperated robot control method based on event triggering and limited time control according to claim 1, characterized in that: The master-side finite time controller is: Where K represents the controller gain coefficient, s m Represents the auxiliary variables of the constructed master robot controller, which is expressed as: in, is the output signal of the master-end zero-order holder, λ is the auxiliary variable gain coefficient of the master-end robot controller; α m represents the damping coefficient of the master controller, 0<σ<1 is the non-integer power of the master controller, κ m is the compensation term of the master robot controller, which is expressed as: Among them, G m (q m ) is the gravity moment compensation item of the master robot; Represents the RBF neural network adaptive term; represents the adaptive compensation term; is the gain weight coefficient matrix of the RBF neural network of the main robot, is the Gaussian function vector of the RBF neural network of the master robot; It is obtained by the following formula: Among them, l represents the number of intermediate nodes of the main-end RBF neural network, x m is the input vector of the main RBF neural network, c mi is the center vector of the ith Gaussian function of the main RBF neural network, b m is the width of the Gaussian function; They are obtained through the following master controller learning laws: Γ m1 , Γ m2 Learning law coefficient for the master controller.

4. The teleoperated robot control method based on event triggering and limited time control according to claim 1, characterized in that: The master-side event trigger is: The position signal of the last master robot event trigger output after passing through the zero-order holder is expressed as Combined with the master robot position signal q currently sent to the master robot event trigger m , calculate the master robot event trigger error e mE (t) is: When the master robot event triggers the error e mE (t) satisfies the following event triggering policy conditions, expressed as: Then the master robot event trigger outputs signal q m , and output the position signal to the communication network and transmit it to the slave end; for the above event trigger strategy, λ 12 ,λ 22 >0 is the main robot event trigger coefficient, is the master robot event trigger coefficient, which is expressed as: Among them, k mE is the event trigger weight of the main robot, d m The upper bound of the communication delay from the master robot to the slave robot.

5. The teleoperated robot control method based on event triggering and limited time control according to claim 1 is characterized in that: The slave-side finite time controller is: Where K represents the controller gain coefficient, which is the same as that in the master-side finite time controller, s s Represents the constructed slave robot controller auxiliary variable, which is expressed as: in, is the output signal of the slave-side zero-order holder, λ is the auxiliary variable gain coefficient of the slave-side controller, which is the same as that of the master; α s represents the damping coefficient of the master controller, 0<σ<1 is the non-integer power of the master controller, κ s is the compensation term of the master robot controller, which is expressed as: Among them, G s (q s ) is the gravity moment compensation item of the master robot; represents the adaptive term of the slave robot RBF neural network; represents the adaptive compensation item of the slave robot; is the gain weight coefficient matrix of the slave robot RBF neural network, is the Gaussian meter function vector of the slave robot RBF neural network; It is obtained by the following formula: Among them, l represents the number of intermediate nodes of the slave RBF neural network, x s is the input vector of the slave RBF neural network, c si is the center vector of the i-th Gaussian function of the slave RBF neural network, b s is the width of the Gaussian function of the slave controller; They are obtained through the following slave controller learning law: Γ s1 , Γ s2 Learning law coefficient for slave controller.

6. The teleoperated robot control method based on event triggering and limited time control according to claim 1, characterized in that: The slave event trigger is: The position signal of the last output from the slave robot event trigger after passing through the zero-order holder is expressed as Combined with the master robot position signal q currently sent to the master robot event trigger s , calculate the master robot event trigger error e sE (t) is: When the master event triggers the error e sE (t) satisfies the following event triggering policy conditions, expressed as: Then the slave robot event trigger outputs signal q s , and output the position signal to the communication network and transmit it to the master end; for the above event trigger strategy, λ2, λ 22 >0 is the event trigger coefficient of the slave robot. is the event trigger coefficient of the slave robot, which is expressed as: Among them, k sE is the event trigger weight of the slave robot, d s is the upper bound of the communication delay from the slave robot to the master robot.

Images