Open Access

ARTICLE

An Adaptive Fuzzy Control Model for Multi-Joint Manipulators

Yanzan Han^1,*, Huawen Zhang¹, Zengfang Shi¹, Shuang Liang²

1 Department of Mechanical and Electrical, Henan Polytechnic Institute, Nanyang, 473000, China
2 University of Florence, Firenze, 50041, Italy

* Corresponding Author: Yanzan Han. Email:

Computer Systems Science and Engineering 2022, 40(3), 1043-1057. https://doi.org/10.32604/csse.2022.017742

Received 09 February 2021; Accepted 13 April 2021; Issue published 24 September 2021

Abstract

Multi-joint manipulator systems are subject to nonlinear influences such as frictional characteristics, random disturbances and load variations. To account for uncertain disturbances in the operation of manipulators, we propose an adaptive manipulator control method based on a multi-joint fuzzy system, in which the upper bound information of the fuzzy system is constant and the state variables of the manipulator control system are measurable. The control algorithm of the system is a MIMO (multi-input-multi-output) fuzzy system that can approximate system error by using a robust adaptive control law to eliminate the shadow caused by approximation error. It can ensure the stability of complex manipulator control systems and reduce the number of fuzzy rules required. Comparison of experimental and simulation data shows that the controller designed using this algorithm has highly-precise trajectory-tracking control and can control robotic systems with complex characteristics of non-linearity, coupling and uncertainty. Therefore, the proposed algorithm has good practical application prospects and promotes the development of complex control systems.

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Keywords

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