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CONTROLLING robot manipulators BY DYNAMIC PROGRAMMING

Acta Mechanica Sinica 1995年第1期11卷 20-33页

作者： MarcJ.Richard Department

A certain number of considerations should be taken into account in the dynamic control of robot manipulators as highly complex non-linear *** this article,we provide a detailed presentation of the mechanical and electrical impli- cations of robots equipped with DC motor *** model takes into account all non-linear aspects of the ***,we develop computational algorithms for optimal control based on dynamic *** robot's trajectory must be predefined,but performance criteria and constraints applying to the system are not limited and we may adapt them freely to the robot and the task being *** an example,a manipulator arm with 3 degrees of freedom is analyzed.

关键词： dynamic programming robot manipulators optimal control dynamic modelling method

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Higher-order Adaptive Iterative Control for Uncertain robot manipulators

Higher-order Adaptive Iterative Control for Uncertain Robot ...

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第二十六届中国控制会议

作者： Quan Quan,Wang Xinhua,Cai Kaiyuan School of Automation Science and Electrical Engineering,Beihang University,Beijing 100083,P.R.China

This paper presents higher-order adaptive iterative learning control for trajectory tracking of uncertain robot ma- *** proposed control schemes have been given rigorous proof of convergence under some *** schemes are based upon the use of a proportional-derivative （PD） feedback structure,for which an iterative term is added to cope with the unknown parameters and ***-order adaptive iterative learning control has potential to give a better convergence performance than the first-order scheme algorithms ,because of using past system control information from more than one past iterative *** effectiveness of the proposed method is shown through numerical simulation results.

关键词： Adaptive iterative control robot manipulators

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Alignment Condition-Based Adaptive Iterative Learning Control for robot manipulators

Alignment Condition-Based Adaptive Iterative Learning Contro...

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第26届中国控制与决策会议

作者： Qiang Chen Fangzheng Xue School of Automation Chongqing University

ISBN: (纸本)9781479937097

In this work, a novel adaptive iterative learning control scheme is designed for robot manipulators with uncertain parameter and external perturbation under alignment condition. The analysis of convergence of proposed control law is based on composite energy function in the iteration domain containing position tracking error, velocity tracking error and parameter estimation error along both the time and iteration axis. Rigorous analysis indicate that both position tracking error and velocity tracking error converge to zero under alignment condition by compensation for the uncertain disturbances. Simulation results also confirm and verify the effectiveness of the proposed method.

关键词： Adaptive iterative learning control robot manipulators Alignment condition Composite energy function

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On the Recursive Implementation of Adaptive Control for robot manipulators

On the Recursive Implementation of Adaptive Control for Robo...

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第二十九届中国控制会议

作者： WANG Hanlei National Key Laboratory of Science and Technology on Space Intelligent Control,Beijing Institute of Control Engineering,Beijing 100190,P.R.China

This paper investigates the recursive implementation of adaptive control for robot *** the spatial vector tool and exploiting some physical properties of multi-body systems,we propose a general framework on the seeking of the Coriolis and centripetal matrix which satisfies the so-called skew-symmetric *** two existing choices are analyzed and a new kind of Coriolis and centripetal matrix is *** between these choices show that the simplest-form Coriolis and centripetal matrix comes from the original recursive Newton-Euler dynamics based on spatial vectors,which implies that skew-symmetric property is an inherent property possessed by spatial-vector based recursive Newton-Euler dynamics *** the proposed general framework regarding establishment of the Coriolis and centripetal matrix,a class of recursive passivity based adaptive algorithms have been *** the next,we present an algorithm on how to derive the filtered manipulator torque *** this filtered torque,the prediction error of the filtered torque is obtained and injected to the direct adaptation,forming the well-known composite adaptation *** adaptation driven by both the tracking errors and the prediction errors gives more smooth tracking error response and estimated parameter response,and also better tracking accuracy.A six-DOF manipulator is employed as a simulation example to show the performance of the proposed recursive algorithms.

关键词： Adaptive Control Recursive Implementation robot manipulators Uncertainties Passivity

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Adaptive Control of a Two-Link robot Using Batch Least-Square Identifier

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IEEE/CAA Journal of Automatica Sinica 2021年第1期8卷 86-93页

作者： Mostafa Bagheri Iasson Karafyllis Peiman Naseradinmousavi Miroslav Krstić the Department of Mechanical and Aerospace Engineering University of California San Diego and San Diego State UniversityLa JollaCA 92037 USA the Department of Mathematics National Technical University of AthensAthina 10682Greece the Department of Mechanical Engineering San DiegoCA 92182 USA the Department of Mechanical and Aerospace Engineering University of California San DiegoLa JollaCA 92037 USA

We design a regulation-triggered adaptive controller for robot manipulators to efficiently estimate unknown parameters and to achieve asymptotic stability in the presence of coupled *** manipulators are widely used in telemanipulation systems where they are subject to model and environmental *** conventional control algorithms on such systems can cause not only poor control performance,but also expensive computational costs and catastrophic ***,system uncertainties need to be estimated through designing a computationally efficient adaptive control *** focus on robot manipulators as an example of a highly nonlinear *** a case study,a 2-DOF manipulator subject to four parametric uncertainties is ***,the dynamic equations of the manipulator are derived,and the corresponding regressor matrix is constructed for the unknown *** a general nonlinear system,a theorem is presented to guarantee the asymptotic stability of the system and the convergence of parameters'***,simulation results are discussed for a two-link manipulator,and the performance of the proposed scheme is thoroughly evaluated.

关键词： Backstepping least-square identifier robot manipulators trigger-based adaptive control

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Optimum Selection of Mechanism Type for Heavy manipulators Based on Particle Swarm Optimization Method

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Chinese Journal of Mechanical Engineering 2013年第4期26卷 763-770页

作者： ZHAO Yong CHEN Genliang WANG Hao LIN Zhongqin State Key Laboratory of Mechanical System and Vibration Shanghai Jiao Tong University Shanghai Key Laboratory of Thin-wall Structure Manufacturing Technology Shanghai Jiao Tong University

The mechanism type plays a decisive role in the mechanical performance of robotic manipulators. Feasible mechanism types can be obtained by applying appropriate type synthesis theory, but there is still a lack of effective and efficient methods for the optimum selection among different types of mechanism candidates. This paper presents a new strategy for the purpose of optimum mechanism type selection based on the modified particle swarm optimization method. The concept of sub-swarm is introduced to represent the different mechanisms generated by the type synthesis, and a competitive mechanism is employed between the sub-swarms to reassign their population size according to the relative performances of the mechanism candidates to implement the optimization. Combining with a modular modeling approach for fast calculation of the performance index of the potential candidates, the proposed method is applied to determine the optimum mechanism type among the potential candidates for the desired manipulator. The effectiveness and efficiency of the proposed method is demonstrated through a case study on the optimum selection of mechanism type of a heavy manipulator where six feasible candidates are considered with force capability as the specific performance index. The optimization result shows that the fitness of the optimum mechanism type for the considered heavy manipulator can be up to 0.578 5. This research provides the instruction in optimum selection of mechanism types for robotic manipulators.

关键词： robot manipulators performance analysis type selection particle swarm optimization

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Neural Control of robotic Manipulator with Guaranteed Tracking Precision and Velocity Constraints 36

Neural Control of Robotic Manipulator with Guaranteed Tracki...

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第36届中国控制会议

作者： Min Wang Yanwen Zhang School of Automation Science and Engineering Guangzhou Key Laboratory of Brain Computer Interaction and ApplicationsSouth China University of Technology

ISBN: (纸本)9781538629185

This paper focuses on adaptive neural control design for n-link robot manipulator systems in the presence of tracking error and velocity state constraints.A performance function is utilized to characterize the prescribed performance of the tracking error.A new transformed function is used to guarantee that tracking errors satisfy the prescribed performance and the velocity states are not to violate their *** designed transformed function is not only of simple structure,but also overcomes the possible high-gain control problem caused by the existing transformed ***,a novel adaptive neural control scheme is proposed by combining independently Lyapunov functions *** proposed scheme guarantees all closed-loop signals are uniformly ultimately bounded,the output tracking errors satisfy the prescribed transient and steady-state tracking performances,and the velocity states are ensured to remain in the predefined bounded *** studies on a 2-link robot are performed and the effectiveness of the proposed scheme is illustrated by simulation results.

关键词： Adaptive Neural Control Tracking Error Constraints State Constraints Performance Transformation robot manipulators

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On Iterative Learning Control

On Iterative Learning Control

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第二十二届中国控制会议

作者： D．Rigas Department of Computing Bradford UniversityRichmond RoadBradford BD7 IDP UK

In this paper, we first introduce a relative new control scheme, iterative learning control. Then we review several of iterative learning control approaches and points out the challenging issues. After that we propose an alternative iterative learning control scheme, called parametric iterative learning control approach for non-linear mechanical robot manipulators. The difference with the conventional iterative learning control approach is that the control input profile is learnt in the conventional iterative learning control approach;instead we use and learn the parameter profile in our approach. The proposed method is an extension of adaptive control of robot manipulators 0. The properties of the robot dynamic structure fully studied in 0 are used in the design of the parameter iterative learning law. The stability and convergence of the proposed control scheme are studied in the sense of the Lyapunov stability theory. Finally the simulation study is performed for a two-link manipulator to demonstrate the effectiveness of the proposed method.

关键词： Iterative learning control robot manipulators Adaptive control Stability Convergence

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