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Asymmetric constrained control scheme design with discrete output feedback in unknown robot–environment interaction system

Published online by Cambridge University Press:  09 September 2022

Xinyi Yu ,
Huizhen Luo Open the ORCID record for Huizhen Luo [Opens in a new window] ,
Shuanwu Shi ,
Yan Wei  and
Linlin Ou
Xinyi Yu
Affiliation:
Zhejiang University of Technology College of Information Engineering, Hangzhou 310023, China
Huizhen Luo
Affiliation:
Zhejiang University of Technology College of Information Engineering, Hangzhou 310023, China
Shuanwu Shi
Affiliation:
Zhejiang University of Technology College of Information Engineering, Hangzhou 310023, China
Yan Wei
Affiliation:
Zhejiang University of Technology College of Information Engineering, Hangzhou 310023, China
Linlin Ou*
Affiliation:
Zhejiang University of Technology College of Information Engineering, Hangzhou 310023, China
*
*Corresponding author: E-mail: linlinou@zjut.edu.cn
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Abstract

In this paper, an overall structure with the asymmetric constrained controller is constructed for human–robot interaction in uncertain environments. The control structure consists of two decoupling loops. In the outer loop, a discrete output feedback adaptive dynamics programing (OPFB ADP) algorithm is proposed to deal with the problems of unknown environment dynamic and unobservable environment position. Besides, a discount factor is added to the discrete OPFB ADP algorithm to improve the convergence speed. In the inner loop, a constrained controller is developed on the basis of asymmetric barrier Lyapunov function, and a neural network method is applied to approximate the dynamic characteristics of the uncertain system model. By utilizing this controller, the robot can track the prescribed trajectory precisely within a security boundary. Simulation and experimental results demonstrate the effectiveness of the proposed controller.

Keywords

discrete output feedbackAdaptive dynamic programingNeural networkAsymmetric barrier Lyapunov functionHuman–robot interaction
Type
Research Article
Information
Robotica , Volume 41 , Issue 1 , January 2023 , pp. 105 - 125
Copyright
© The Author(s), 2022. Published by Cambridge University Press

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