A composite nonlinear feedback tracking controller for motion control of robot manipulators is described. The structure of the controller is composed of a composite nonlinear feedback law plus full robot nonlinear dyn...A composite nonlinear feedback tracking controller for motion control of robot manipulators is described. The structure of the controller is composed of a composite nonlinear feedback law plus full robot nonlinear dynamics compensation. The stability is carried out in the presence of friction. The controller takes advantage of varying damping ratios induced by the composite nonlinear feedback control, so the transient performance of the closed-loop is remarkably improved. Simulation results demonstrate the feasibility of the proposed method.展开更多
Because of its ease of implementation,a linear PID controller is generally used to control robotic manipulators.Linear controllers cannot effectively cope with uncertainties and variations in the parameters;therefore,...Because of its ease of implementation,a linear PID controller is generally used to control robotic manipulators.Linear controllers cannot effectively cope with uncertainties and variations in the parameters;therefore,nonlinear controllers with robust performance which can cope with these are recommended.The sliding mode control(SMC)is a robust state feedback control method for nonlinear systems that,in addition having a simple design,efficiently overcomes uncertainties and disturbances in the system.It also has a very fast transient response that is desirable when controlling robotic manipulators.The most critical drawback to SMC is chattering in the control input signal.To solve this problem,in this study,SMC is used with a boundary layer(SMCBL)to eliminate the chattering and improve the performance of the system.The proposed SMCBL was compared with inverse dynamic control(IDC),a conventional nonlinear control method.The kinematic and dynamic equations of the IRB-120 robot manipulator were initially extracted completely and accurately,and then the control of the robot manipulator using SMC was evaluated.For validation,the proposed control method was implemented on a 6-DOF IRB-120 robot manipulator in the presence of uncertainties.The results were simulated,tested,and compared in the MATLAB/Simulink environment.To further validate our work,the results were tested and confirmed experimentally on an actual IRB-120 robot manipulator.展开更多
Considering the compliance control problem of a hexapod robot under different environments, a control strategy based on the improved adaptive control algorithm is proposed. The model of robot structure and impedance c...Considering the compliance control problem of a hexapod robot under different environments, a control strategy based on the improved adaptive control algorithm is proposed. The model of robot structure and impedance control is established. Then, the indirect adaptive control algorithm is derived. Through the analysis of its parameters, it can be noticed that the algorithm does not meet the requirements of the robot compliance control in a complex environment. Therefore, the fuzzy control algorithm is used to adjust the adaptive control parameters. The satisfied system response can be obtained based on the adjustment in real time according to the error between input and output. Comparative experiments and analysis of traditional adaptive control and the improved adaptive control algorithm are presented. It can be verified that not only desired contact force can be reached quickly in different environments, but also smaller contact impact and sliding avoidance are guaranteed, which means that the control strategy has great significance to enhance the adaptability of the hexapod robot.展开更多
A practical motion control strategy for a radio-controlled, 4-link and free-swimmingbiomimetic robot fish is presented. Based on control performance of the fish the fish s motion controltask is decomposed into on-line...A practical motion control strategy for a radio-controlled, 4-link and free-swimmingbiomimetic robot fish is presented. Based on control performance of the fish the fish s motion controltask is decomposed into on-line speed control and orientation control. The speed control algorithm isimplemented by using piecewise control, and orientation control is realized by fuzzy logic. Combiningwith step control and fuzzy control, a point-to-point (PTP) control algorithm is proposed and appliedto the closed-loop experimental system that uses a vision-based position sensing subsystem to providefeedback. Experiments confirm the reliability and e?ectiveness of the presented algorithms.展开更多
In order to mitigate the effects of space adaptation syndrome(SAS) and improve the training efficiency of the astronauts, a novel astronaut rehabilitative training robot(ART) was proposed. ART can help the astronauts ...In order to mitigate the effects of space adaptation syndrome(SAS) and improve the training efficiency of the astronauts, a novel astronaut rehabilitative training robot(ART) was proposed. ART can help the astronauts to carry out the bench press training in the microgravity environment. Firstly, a dynamic model of cable driven unit(CDU) was established whose accuracy was verified through the model identification. Secondly, to improve the accuracy and the speed of the active loading, an active loading hybrid force controller was proposed on the basis of the dynamic model of the CDU. Finally, the actual effect of the hybrid force controller was tested by simulations and experiments. The results suggest that the hybrid force controller can significantly improve the precision and the dynamic performance of the active loading with the maximum phase lag of the active loading being 9° and the maximum amplitude error being 2% at the frequency range of 10 Hz. The controller can meet the design requirements.展开更多
The semi-round rigid feet would cause position-posture deviation problem because the actual foothold position is hardly known due to the rolling effect of the semi-round rigid feet during the robot walking. The positi...The semi-round rigid feet would cause position-posture deviation problem because the actual foothold position is hardly known due to the rolling effect of the semi-round rigid feet during the robot walking. The position-posture deviation problem may harm to the stability and the harmony of the robot, or even makes the robot tip over and fail to walk forward. Focused on the position-posture deviation problem of multi-legged walking robots with semi-round rigid feet, a new method of position-posture closed-loop control is proposed to solve the position-posture deviation problem caused by semi-round rigid feet, based on the inverse velocity kinematics of the multi-legged walking robots. The position-posture closed-loop control is divided into two parts: the position closed-loop control and the posture closed-loop control. Thus, the position-posture control for the robot which is a tight coupling and nonlinear system is decoupled. Co-simulations of position-posture open-loop control and position-posture closed-loop control by MATLAB and ADAMS are implemented, respectively. The co-simulation results verify that the position-posture closed-loop control performs well in solving the position-posture deviation problem caused by semi-round rigid feet.展开更多
A learning-based control approach is presented for force servoing of a robot with vision in an unknown environment. Firstly, mapping relationships between image features of the servoing object and the joint angles of ...A learning-based control approach is presented for force servoing of a robot with vision in an unknown environment. Firstly, mapping relationships between image features of the servoing object and the joint angles of the robot are derived and learned by a neural network. Secondly, a learning controller based on the neural network is designed for the robot to trace the object. Thirdly, a discrete time impedance control law is obtained for the force servoing of the robot, the on-line learning algorithms for three neural networks are developed to adjust the impedance parameters of the robot in the unknown environment. Lastly, wiping experiments are carried out by using a 6 DOF industrial robot with a CCD camera and a force/torque sensor in its end effector, and the experimental results confirm the effecti veness of the approach.展开更多
An improved hybrid position/force controller design of a flexible robot manipulator is presented using a sliding observer. The friction between the end effector and the environment is considered and compensated. For s...An improved hybrid position/force controller design of a flexible robot manipulator is presented using a sliding observer. The friction between the end effector and the environment is considered and compensated. For systematic reasons the controller is designed taking into consideration the rigid link subsystems and the flexible joints. The proposed control system satisfies the stability of the two subsystems and copes with the uncertainty of robot dynamics. A sliding observer is designed to estimate the time derivative of the torque applied as input to the rigid part of the robot. For the stability of the observer, it is assumed that the uncertainty of the observed system is bounded. A MRAC algorithm is used for the estimation of the friction forces at the contact point between the end effector and the environment. Finally simulation and experimental results are given, to demonstrate the effectiveness of the proposed controller.展开更多
Force control based on neural networks is presented. Under the framework of hybrid control, an RBF neural network is used to compensate for all the uncertainties from robot dynamics and unknown environment first. The ...Force control based on neural networks is presented. Under the framework of hybrid control, an RBF neural network is used to compensate for all the uncertainties from robot dynamics and unknown environment first. The technique will improve the adaptability to environment stiffness when the end-effector is in contact with the environment, and does not require any a priori knowledge on the upper bound of syste uncertainties. Moreover, it need not compute the inverse of inertia matrix. Learning algorithms for neural networks to minimize the force error directly are designed. Simulation results have shown a better force/position tracking when neural network is used.展开更多
Since the joint actuator of the space robot executes the control instructions frequently in the harsh space environment,it is prone to the partial loss of control effectiveness(PLCE)fault.An adaptive fault-tolerant co...Since the joint actuator of the space robot executes the control instructions frequently in the harsh space environment,it is prone to the partial loss of control effectiveness(PLCE)fault.An adaptive fault-tolerant control algorithm is designed for a space robot system with the uncertain parameters and the PLCE actuator faults.The mathematical model of the system is established based on the Lagrange method,and the PLCE actuator fault is described as an effectiveness factor.The lower bound of the effectiveness factors and the upper bound of the uncertain parameters are estimated by an adaptive strategy,and the estimated value is fed back to the control algorithm.Compared with the traditional fault-tolerant algorithms,the proposed algorithm does not need to predetermine the lower bound of the effectiveness factor,hence it is more in line with the actual engineering application.It is proved that the algorithm can guarantee the stability of the closed-loop system based on the Lyapunov function method.The numerical simulation results show that the proposed algorithm can not only compensate for the uncertain parameters,but also can tolerate the PLCE actuator faults effectively,which verifies the effectiveness and superiority of the control scheme.展开更多
Industrial robot system is a kind of dynamic system w ith strong nonlinear coupling and high position precision. A lot of control ways , such as nonlinear feedbackdecomposition motion and adaptive control and so o n, ...Industrial robot system is a kind of dynamic system w ith strong nonlinear coupling and high position precision. A lot of control ways , such as nonlinear feedbackdecomposition motion and adaptive control and so o n, have been used to control this kind of system, but there are some deficiencie s in those methods: some need accurate and some need complicated operation and e tc. In recent years, in need of controlling the industrial robots, aiming at com pletely tracking the ideal input for the controlled subject with repetitive character, a new research area, ILC (iterative learning control), has been devel oped in the control technology and theory. The iterative learning control method can make the controlled subject operate as desired in a definite time span, merely making use of the prior control experie nce of the system and searching for the desired control signal according to the practical and desired output signal. The process of searching is equal to that o f learning, during which we only need to measure the output signal to amend the control signal, not like the adaptive control strategy, which on line assesses t he complex parameters of the system. Besides, since the iterative learning contr ol relies little on the prior message of the subject, it has been well used in a lot of areas, especially the dynamic systems with strong non-linear coupling a nd high repetitive position precision and the control system with batch producti on. Since robot manipulator has the above-mentioned character, ILC can be very well used in robot manipulator. In the ILC, since the operation always begins with a certain initial state, init ial condition has been required in almost all convergence verification. Therefor e, in designing the controller, the initial state has to be restricted with some condition to guarantee the convergence of the algorithm. The settle of initial condition problem has long been pursued in the ILC. There are commonly two kinds of initial condition problems: one is zero initial error problem, another is non-zero initial error problem. In practice, the repe titive operation will invariably produce excursion of the iterative initial stat e from the desired initial state. As a result, the research on the second in itial problem has more practical meaning. In this paper, for the non-zero initial error problem, one novel robust ILC alg orithms, respectively combining PD type iterative learning control algorithm wit h the robust feedback control algorithm, has been presented. This novel robust ILC algorithm contain two parts: feedforward ILC algorithm and robust feedback algorithm, which can be used to restrain disturbance from param eter variation, mechanical nonlinearities and unmodeled dynamics and to achieve good performance as well. The feedforward ILC algorithm can be used to improve the tracking error and perf ormance of the system through iteratively learning from the previous operation, thus performing the tracking task very fast. The robust feedback algorithm could mainly be applied to make the real output of the system not deviate too much fr om the desired tracking trajectory, and guarantee the system’s robustness w hen there are exterior noises and variations of the system parameter. In this paper, in order to analyze the convergence of the algorithm, Lyapunov st ability theory has been used through properly selecting the Lyapunov function. T he result of the verification shows the feasibility of the novel robust iterativ e learning control in theory. Finally, aiming at the two-freedom rate robot, simulation has been made with th e MATLAB software. Furthermore, two groups of parameters are selected to validat e the robustness of the algorithm.展开更多
基金supported by the National Natural Science Foundation of China (60428303)
文摘A composite nonlinear feedback tracking controller for motion control of robot manipulators is described. The structure of the controller is composed of a composite nonlinear feedback law plus full robot nonlinear dynamics compensation. The stability is carried out in the presence of friction. The controller takes advantage of varying damping ratios induced by the composite nonlinear feedback control, so the transient performance of the closed-loop is remarkably improved. Simulation results demonstrate the feasibility of the proposed method.
文摘Because of its ease of implementation,a linear PID controller is generally used to control robotic manipulators.Linear controllers cannot effectively cope with uncertainties and variations in the parameters;therefore,nonlinear controllers with robust performance which can cope with these are recommended.The sliding mode control(SMC)is a robust state feedback control method for nonlinear systems that,in addition having a simple design,efficiently overcomes uncertainties and disturbances in the system.It also has a very fast transient response that is desirable when controlling robotic manipulators.The most critical drawback to SMC is chattering in the control input signal.To solve this problem,in this study,SMC is used with a boundary layer(SMCBL)to eliminate the chattering and improve the performance of the system.The proposed SMCBL was compared with inverse dynamic control(IDC),a conventional nonlinear control method.The kinematic and dynamic equations of the IRB-120 robot manipulator were initially extracted completely and accurately,and then the control of the robot manipulator using SMC was evaluated.For validation,the proposed control method was implemented on a 6-DOF IRB-120 robot manipulator in the presence of uncertainties.The results were simulated,tested,and compared in the MATLAB/Simulink environment.To further validate our work,the results were tested and confirmed experimentally on an actual IRB-120 robot manipulator.
基金Project(51221004) supported by the Science Fund for Creative Research Groups of National Natural Science Foundation of ChinaProject(2010R50036) supported by the Program for Zhejiang Leading Team of S&T Innovation,China
文摘Considering the compliance control problem of a hexapod robot under different environments, a control strategy based on the improved adaptive control algorithm is proposed. The model of robot structure and impedance control is established. Then, the indirect adaptive control algorithm is derived. Through the analysis of its parameters, it can be noticed that the algorithm does not meet the requirements of the robot compliance control in a complex environment. Therefore, the fuzzy control algorithm is used to adjust the adaptive control parameters. The satisfied system response can be obtained based on the adjustment in real time according to the error between input and output. Comparative experiments and analysis of traditional adaptive control and the improved adaptive control algorithm are presented. It can be verified that not only desired contact force can be reached quickly in different environments, but also smaller contact impact and sliding avoidance are guaranteed, which means that the control strategy has great significance to enhance the adaptability of the hexapod robot.
基金Supported by the Scientific Research Foundation for the Returned 0verseas Chinese Scholars, State Education Ministry, and National Natural Science Foundation of China （60474005）
文摘A practical motion control strategy for a radio-controlled, 4-link and free-swimmingbiomimetic robot fish is presented. Based on control performance of the fish the fish s motion controltask is decomposed into on-line speed control and orientation control. The speed control algorithm isimplemented by using piecewise control, and orientation control is realized by fuzzy logic. Combiningwith step control and fuzzy control, a point-to-point (PTP) control algorithm is proposed and appliedto the closed-loop experimental system that uses a vision-based position sensing subsystem to providefeedback. Experiments confirm the reliability and e?ectiveness of the presented algorithms.
基金Project(61175128) supported by the National Natural Science Foundation of ChinaProject(2008AA040203) supported by the National High Technology Research and Development Program of ChinaProject(QC2010009) supported by the Natural Science Foundation of Heilongjiang Province,China
文摘In order to mitigate the effects of space adaptation syndrome(SAS) and improve the training efficiency of the astronauts, a novel astronaut rehabilitative training robot(ART) was proposed. ART can help the astronauts to carry out the bench press training in the microgravity environment. Firstly, a dynamic model of cable driven unit(CDU) was established whose accuracy was verified through the model identification. Secondly, to improve the accuracy and the speed of the active loading, an active loading hybrid force controller was proposed on the basis of the dynamic model of the CDU. Finally, the actual effect of the hybrid force controller was tested by simulations and experiments. The results suggest that the hybrid force controller can significantly improve the precision and the dynamic performance of the active loading with the maximum phase lag of the active loading being 9° and the maximum amplitude error being 2% at the frequency range of 10 Hz. The controller can meet the design requirements.
基金Project(51221004)supported by the Science Fund for Creative Research Groups of National Natural Science Foundation of ChinaProject supported by the Program for Zhejiang Leading Team of S&T Innovation,China
文摘The semi-round rigid feet would cause position-posture deviation problem because the actual foothold position is hardly known due to the rolling effect of the semi-round rigid feet during the robot walking. The position-posture deviation problem may harm to the stability and the harmony of the robot, or even makes the robot tip over and fail to walk forward. Focused on the position-posture deviation problem of multi-legged walking robots with semi-round rigid feet, a new method of position-posture closed-loop control is proposed to solve the position-posture deviation problem caused by semi-round rigid feet, based on the inverse velocity kinematics of the multi-legged walking robots. The position-posture closed-loop control is divided into two parts: the position closed-loop control and the posture closed-loop control. Thus, the position-posture control for the robot which is a tight coupling and nonlinear system is decoupled. Co-simulations of position-posture open-loop control and position-posture closed-loop control by MATLAB and ADAMS are implemented, respectively. The co-simulation results verify that the position-posture closed-loop control performs well in solving the position-posture deviation problem caused by semi-round rigid feet.
基金This project was supported by the research foundation of China Education Ministry for the scholars from abroad (2002247).
文摘A learning-based control approach is presented for force servoing of a robot with vision in an unknown environment. Firstly, mapping relationships between image features of the servoing object and the joint angles of the robot are derived and learned by a neural network. Secondly, a learning controller based on the neural network is designed for the robot to trace the object. Thirdly, a discrete time impedance control law is obtained for the force servoing of the robot, the on-line learning algorithms for three neural networks are developed to adjust the impedance parameters of the robot in the unknown environment. Lastly, wiping experiments are carried out by using a 6 DOF industrial robot with a CCD camera and a force/torque sensor in its end effector, and the experimental results confirm the effecti veness of the approach.
基金Supported by National Natural Science Foundation of P.R.China(50405046,60605028)Shanghai Project of International Cooperation(045107031)the Program for Excellent Young Teachers of Shanghai(04YOHB094)
文摘An improved hybrid position/force controller design of a flexible robot manipulator is presented using a sliding observer. The friction between the end effector and the environment is considered and compensated. For systematic reasons the controller is designed taking into consideration the rigid link subsystems and the flexible joints. The proposed control system satisfies the stability of the two subsystems and copes with the uncertainty of robot dynamics. A sliding observer is designed to estimate the time derivative of the torque applied as input to the rigid part of the robot. For the stability of the observer, it is assumed that the uncertainty of the observed system is bounded. A MRAC algorithm is used for the estimation of the friction forces at the contact point between the end effector and the environment. Finally simulation and experimental results are given, to demonstrate the effectiveness of the proposed controller.
文摘Force control based on neural networks is presented. Under the framework of hybrid control, an RBF neural network is used to compensate for all the uncertainties from robot dynamics and unknown environment first. The technique will improve the adaptability to environment stiffness when the end-effector is in contact with the environment, and does not require any a priori knowledge on the upper bound of syste uncertainties. Moreover, it need not compute the inverse of inertia matrix. Learning algorithms for neural networks to minimize the force error directly are designed. Simulation results have shown a better force/position tracking when neural network is used.
基金supported by the National Natural Science Foundation of China(11372073,11072061)
文摘Since the joint actuator of the space robot executes the control instructions frequently in the harsh space environment,it is prone to the partial loss of control effectiveness(PLCE)fault.An adaptive fault-tolerant control algorithm is designed for a space robot system with the uncertain parameters and the PLCE actuator faults.The mathematical model of the system is established based on the Lagrange method,and the PLCE actuator fault is described as an effectiveness factor.The lower bound of the effectiveness factors and the upper bound of the uncertain parameters are estimated by an adaptive strategy,and the estimated value is fed back to the control algorithm.Compared with the traditional fault-tolerant algorithms,the proposed algorithm does not need to predetermine the lower bound of the effectiveness factor,hence it is more in line with the actual engineering application.It is proved that the algorithm can guarantee the stability of the closed-loop system based on the Lyapunov function method.The numerical simulation results show that the proposed algorithm can not only compensate for the uncertain parameters,but also can tolerate the PLCE actuator faults effectively,which verifies the effectiveness and superiority of the control scheme.
文摘Industrial robot system is a kind of dynamic system w ith strong nonlinear coupling and high position precision. A lot of control ways , such as nonlinear feedbackdecomposition motion and adaptive control and so o n, have been used to control this kind of system, but there are some deficiencie s in those methods: some need accurate and some need complicated operation and e tc. In recent years, in need of controlling the industrial robots, aiming at com pletely tracking the ideal input for the controlled subject with repetitive character, a new research area, ILC (iterative learning control), has been devel oped in the control technology and theory. The iterative learning control method can make the controlled subject operate as desired in a definite time span, merely making use of the prior control experie nce of the system and searching for the desired control signal according to the practical and desired output signal. The process of searching is equal to that o f learning, during which we only need to measure the output signal to amend the control signal, not like the adaptive control strategy, which on line assesses t he complex parameters of the system. Besides, since the iterative learning contr ol relies little on the prior message of the subject, it has been well used in a lot of areas, especially the dynamic systems with strong non-linear coupling a nd high repetitive position precision and the control system with batch producti on. Since robot manipulator has the above-mentioned character, ILC can be very well used in robot manipulator. In the ILC, since the operation always begins with a certain initial state, init ial condition has been required in almost all convergence verification. Therefor e, in designing the controller, the initial state has to be restricted with some condition to guarantee the convergence of the algorithm. The settle of initial condition problem has long been pursued in the ILC. There are commonly two kinds of initial condition problems: one is zero initial error problem, another is non-zero initial error problem. In practice, the repe titive operation will invariably produce excursion of the iterative initial stat e from the desired initial state. As a result, the research on the second in itial problem has more practical meaning. In this paper, for the non-zero initial error problem, one novel robust ILC alg orithms, respectively combining PD type iterative learning control algorithm wit h the robust feedback control algorithm, has been presented. This novel robust ILC algorithm contain two parts: feedforward ILC algorithm and robust feedback algorithm, which can be used to restrain disturbance from param eter variation, mechanical nonlinearities and unmodeled dynamics and to achieve good performance as well. The feedforward ILC algorithm can be used to improve the tracking error and perf ormance of the system through iteratively learning from the previous operation, thus performing the tracking task very fast. The robust feedback algorithm could mainly be applied to make the real output of the system not deviate too much fr om the desired tracking trajectory, and guarantee the system’s robustness w hen there are exterior noises and variations of the system parameter. In this paper, in order to analyze the convergence of the algorithm, Lyapunov st ability theory has been used through properly selecting the Lyapunov function. T he result of the verification shows the feasibility of the novel robust iterativ e learning control in theory. Finally, aiming at the two-freedom rate robot, simulation has been made with th e MATLAB software. Furthermore, two groups of parameters are selected to validat e the robustness of the algorithm.
