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Robust Iterative Learning Controller for the Non-zero Initial Error Problem on robot manipulator

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厦门大学学报（自然科学版） 2002年第S1期41卷 -页

作者： TAO Li-li 1,YANG Fu-wen 2 (1. Department of Automation, University of Xiamen, Xiamen 361005, Chi na 2. Department of Electrical Engineering, University of Fuzhou, Fuzhou 350002, C hina)

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 pro

关键词： robust control iterative learning control non- zero initial error robot manipulator

Robust H_∞ Control of robot manipulator

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Systems Science and Systems Engineering 1998年第2期8卷 56-62页

作者： HONG Yiguang SHI Aifen QIN Huashu Institute of Systems Sicence Academia SinicaBeijing100080PCR Institute of Systems Engineering of Northern China Beijing 100081.

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１ＩｎｔｒｏｄｕｃｔｉｏｎＡｓｗｅｋｎｏｗ，ｂｅｃａｕｓｅｏｆｅｎｖｉｒｏｎｍｅｎｔａｌｃｏｎｄｉｔｉｏｎｓａｎｄｓｐｅｃｉａｌｄｅｓｉｇｎｄｅｍａｎｄｓ，ｒｏ－ｂｕｓｔｎｅｓｓｆｏｒｒｏｂｏｔｃｏｎｔｒｏｌｂｅｃｏｍｅｍｏｒｅａｎｄｍｏｒｅｉｍｐｏ...

关键词： Robust H∞ control robot manipulator Radial solution.

Segment-wise learning control for trajectory tracking of robot manipulators under iteration-dependent periods

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Science China(Information Sciences) 2024年第3期67卷 155-166页

作者： Fan ZHANG Deyuan MENG Kaiquan CAI The Seventh Research Division Beihang University School of Automation Science and Electrical Engineering Beihang University School of Electronics and Information Engineering Beihang University

This paper is concerned with the amplitude boundedness problem of adaptive iterative learning control(AILC) for robot manipulators operating with iteration-dependent periods. By introducing virtual memory slots for storing historical data, a practical AILC method is proposed to achieve the segmentwise learning. This method requires less memory storage for historical information of previous iterations,especially in comparison with that of the conventional AILC methods using point-wise learning *** is shown that not only the energy boundedness but also the amplitude boundedness of estimates and inputs of practical AILC can be guaranteed. Moreover, the practical AILC method can achieve the perfect tracking objective regardless of iteration-dependent periods when the robot manipulators have a persistent full learning property. In addition, a solution to the visual manipulator platform is provided and deployed based on Coppeliasim and Matlab, which helps to show the amplitude boundedness of learning results and the perfect tracking performances of the proposed practical AILC method for robot manipulators.

关键词： amplitude boundedness iteration-dependent period iterative learning control robot manipulator segment-wise virtual memory slot

Adaptive Tracking Control for Uncertain robot manipulator with Additive Disturbance

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Adaptive Tracking Control for Uncertain Robot Manipulator wi...

第二十六届中国控制会议

作者： Xian Bin School of Electrical Engineering and Automation,Tianjin University,Tianjin 30072,P.R.China

In this paper,we present a continuous control mechanism that compensate the parameter linearizable uncertainty in a 6-link robot manipulator system under both repeating and non-repeating *** control strategy is based on limited assumption on the system nonlinearities.A smei-global asymptotic tracking result is achieved while all the closed-loop states remain bounded.

关键词： robot manipulator Uncertain Disturbance Adaptive Tracking Control

An New Computational Method of the Identification Jacobian for robot manipulator Calibraiton

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An New Computational Method of the Identification Jacobian f...

2011 2nd Asia-Pacific Conference on Wearable Computing Systems

作者： Jianye zhang School of Mechanical Engineering Tianjin University

Identification jacobian matrix, which represents the relationship between kinematic parameter error and the positional error of the robot manipulator, is very useful for the model based calibration of robot manipulator. In this paper, a new methodology to calculate the identification jacobian matrix for robot manipulator calibration is presented based on the modified Khalil and Kleinfinger notation. A computer program to calculate the identification jacobian matrix by using symbolic computation has been developed in MATLAB.

关键词： identification jacobian matrix robot manipulator computation

Type-2 Fuzzy Adaptive Control For Uncertain robot manipulator System With Time-Varying Output Constraints

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Type-2 Fuzzy Adaptive Control For Uncertain Robot Manipulato...

第32届中国控制与决策会议

作者： Yongqing Fan Tongtong Kang School of Automation Xi’an Key Laboratory of Advanced Control and Intelligent ProcessXi’an University of Posts and Telecommunications

A novel adaptive control design method based on type-2 fuzzy logic system is proposed in this *** controller is to solve the stability problem of n-link manipulator system with time-varying output constraints in complex *** the analysis of type-2 fuzzy logic systems,a new and original universal approximator with parameter is proposed to equalize the un-certainties in robot manipulator *** main advantages of this design method one is that the computational burden of online learning can be reduced greatly,another merit is more smaller tracking error can be ensured,and the output or position of the robot manipulator system are constrained by time-varying *** addition to these,the idea of this paper extends the semi-global stability to global stability compares to the traditional fuzzy adaptive *** effectiveness of the method is demonstrated by simulation results.

关键词： Type-2 fuzzy logic system Adaptive control Time-varying output robot manipulator

Tracking Control for robot manipulator Based on Deterministic Learning and Event-Triggered Mechanism

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Tracking Control for Robot Manipulator Based on Deterministi...

第三十九届中国控制会议

作者： Min Wang Rui Hu Xuegang Xin Haotian Shi School of Automation Science and Engineering South China University of Technology School of Medicine South China University of Technology

In this paper, a control scheme is presented for robotic manipulator by combining deterministic learning and eventtriggered mechanism. Notice that the traditional adaptive neural control needs to re-adapt neural network（NN） weights even for performing the same control task, thereby result in the limited learning ability. To enhance the neural leaning ability, a dynamic learning controller is firstly constructed based on the radial basis function（RBF） NN, which has the ability to learn the knowledge of the unknown closed-loop system dynamics. By reusing the learned knowledge, the dynamic learning-based event-triggered control scheme is put forward to achieve a tradeoff between the network resource and the tracking performance. Specially, an easy-to-implemented event-triggered condition is designed by the Lyapunov technique due to the use of experience *** proposed scheme ensures that the tracking error converges to a small neighborhood of the origin, all the signals in the closedloop system are bounded and meanwhile the communication resources are greatly reduced. A comparison simulation example is conducted to demonstrate the effectiveness and advantage of the proposed control scheme.

关键词： Deterministic learning event-triggered mechanism adptive neural control robot manipulator

A New robot manipulator Uncalibrated Visual Serving Control Method

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A New Robot Manipulator Uncalibrated Visual Serving Control ...

2015年中国智能自动化学术会议

作者： Wang Niu Liu Lang Qiu Jing College of Automation Chongqing University

This paper presents a new robot manipulator uncalibrated visual serving control method, which can conduct visual feedback control under the situation that the internal and external of camera parameters and the robot manipulator model are unknown, as well as without real-time computing the inverse of image ***, the dual cameras biaxial parallel vision configuration is applied to detect the posture of the characteristics of robot manipulator end. Then, we select the specific feature points and lines in the image plane in order to represent the five degrees of freedom of the robot manipulator in cartesian space and design a PI ***, we realized the five degrees of freedom of the robot manipulator uncalibrated visual serving control in the actual physical platform, and the experiment results show that the effectiveness of the proposed control method under the dual cameras biaxial parallel vision configuration.

关键词： robot manipulator Uncalibrated visual Biaxial parallel vision configuration Five degrees of freedom PI controller

Fault-tolerant control of a 2-DOF robot manipulator using multi-sensor switching strategy

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Fault-tolerant control of a 2-DOF robot manipulator using mu...

第36届中国控制会议

作者： Yilin Mi Feng Xu Junbo Tan Xueqian Wang Bin Liang Shenzhen Engineering Laboratory of Geometry Measurement Technology Graduate School at ShenzhenTsinghua University

ISBN: (纸本)9781538629185

In this paper,a fault-tolerant multi-sensor switching strategy is used for sensor-fault tolerance of robot manipulator with redundant sensors in each joint to provide the angular position of the *** strategy employs a linear-parameter-varying（LPV） model to describe the nonlinear dynamics of the robot ***,based on the obtained LPV model,a zonotopic set-based robust fault detection（FD） mechanism is further designed to monitor the system *** each time instant,the FD mechanism checks whether there are some sensors that have become faulty to make FD decisions.A switching controller is designed to choose the best estimation among the healthy sensors to generate closed-loop control *** a sensor has become faulty and is detected by the FD mechanism,the fault-tolerant strategy discards the faulty sensor and uses the healthy one to implement closed-loop *** the end,some simulation results are presented to illustrate the effectiveness of the proposed fault-tolerant control（FTC） strategy.

关键词： robot manipulator fault-tolerant control multi-sensor switching scheme bounded sets zonotopes