检索结果-南通市图书馆

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

维普期刊数据库评论

在线全文

维普期刊数据库

学校读者我要写书评

暂无评论

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 strategies.It 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

Robust H_∞ Control of robot manipulator

在线全文

同方期刊数据库

学校读者我要写书评

暂无评论

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.

１ＩｎｔｒｏｄｕｃｔｉｏｎＡｓｗｅｋｎｏｗ，ｂｅｃａｕｓｅｏｆｅｎｖｉｒｏｎｍｅｎｔａｌｃｏｎｄｉｔｉｏｎｓａｎｄｓｐｅｃｉａｌｄｅｓｉｇｎｄｅｍａｎｄｓ，ｒｏ－ｂｕｓｔｎｅｓｓｆｏｒｒｏｂｏｔｃｏｎｔｒｏｌｂｅｃｏ... 详细信息

１ＩｎｔｒｏｄｕｃｔｉｏｎＡｓｗｅｋｎｏｗ，ｂｅｃａｕｓｅｏｆｅｎｖｉｒｏｎｍｅｎｔａｌｃｏｎｄｉｔｉｏｎｓａｎｄｓｐｅｃｉａｌｄｅｓｉｇｎｄｅｍａｎｄｓ，ｒｏ－ｂｕｓｔｎｅｓｓｆｏｒｒｏｂｏｔｃｏｎｔｒｏｌｂｅｃｏｍｅｍｏｒｅａｎｄｍｏｒｅｉｍｐｏ...

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

维普期刊数据库

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

在线全文

学校读者我要写书评

暂无评论

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 problems: one is zero initial error problem, anothe

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

维普期刊数据库

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

在线全文

学校读者我要写书评

暂无评论

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

Disturbance observer based actor-critic learning control for uncertain nonlinear systems

在线全文

cnki会议

学校读者我要写书评

暂无评论

Chinese Journal of Aeronautics 2023年第11期36卷 271-280页

作者： Xianglong LIANG Zhikai YAO Yaowen GE Jianyong YAO School of Mechanical Engineering Nanjing University of Science and TechnologyNanjing 210094China College of Artificial Intelligence Nanjing University of Post and TelecommunicationNanjing 210023China

This paper investigates the disturbance observer based actor-critic learning control for a class of uncertain nonlinear systems in the presence of unmodeled dynamics and time-varying disturbances.The proposed control algorithm integrates a filter-based design method with actor-critic learning architecture and disturbance observer to circumvent the unmodeled dynamic and the timevarying disturbance.To be specific,the actor network is employed to estimate the unknown system dynamic,the critic network is developed to evaluate the control performance,and the disturbance observer is leveraged to provide efficient estimation of the compounded disturbance which includes the time-varying disturbance and the actor-critic network approximation error.Consequently,highgain feedback is avoided and the improved tracking performance can be expected.Moreover,a composite weight adaptation law for actor network is constructed by utilizing two types of signals,the cost function and the modeling error.Eventually,theoretical analysis demonstrates that the developed controller can guarantee bounded stability.Extensive simulations and experiments on a robot manipulator are implemented to validate the performance of the resulted control strategy.

关键词： Actor-critic structure Composite adaptation Disturbance observer robot manipulator Uncertain nonlinear system

维普期刊数据库

Novel sliding-mode disturbance observer-based tracking control with applications to robot manipulators

在线全文

学校读者我要写书评

暂无评论

Science China(Information Sciences) 2021年第7期64卷 80-91页

作者： Tairen SUN Long CHENG Zengguang HOU Min TAN School of Electrical and Information Engineering Jiangsu University State Key Laboratory of Management and Control for Complex Systems Institute of AutomationChinese Academy of Sciences School of Artificial Intelligence University of Chinese Academy of Sciences

This paper proposes a sliding-mode disturbance observer(SMDOB)-based tracking controller for a class of nonlinear systems with modeling uncertainties and external disturbances. The SMDOB is constructed using an extended state observer embedded by a filtered sliding mode term. The chattering caused by the sliding mode is compressed by the frequency bandwidths of both the extended state observer and the control system. The novelties of the proposed controller are as follows:(1) The semiglobal asymptotical stability of the combined controller-observer system is guaranteed without the boundedness assumption of the time derivatives of modeling uncertainties;(2) the SMDOB can be implemented with a low complexity because of only three parameters to be tuned. Applications to robot manipulators illustrate the effectiveness of the SMDOB-based tracking control strategy.

关键词： adaptive control robot manipulator disturbance observer sliding mode

Adaptive Tracking Control for Uncertain robot manipulator with Additive Disturbance

在线全文

同方期刊数据库

学校读者我要写书评

暂无评论

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 disturbance.The 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

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

在线全文

cnki会议

学校读者我要写书评

暂无评论

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 paper.The controller is to solve the stability problem of n-link manipulator system with time-varying output constraints in complex environment.Through 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 system.The 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 output.In addition to these,the idea of this paper extends the semi-global stability to global stability compares to the traditional fuzzy adaptive controls.The 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

在线全文

cnki会议

学校读者我要写书评

暂无评论

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 knowledge.The 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