Title: Three controllers via 2nd-order sliding mode for leader-following formation control of multi-robot systems

Authors: Jiarong Chen; Dianwei Qian

Addresses: School of Control and Computer Engineering, North China Electric Power University, Changping District, Beijing 102206, China ' School of Control and Computer Engineering, North China Electric Power University, Changping District, Beijing 102206, China

Abstract: The multi-robot formation has always been an attractive field for cooperative control of robots. This paper uses the improved second-order sliding mode method to control the leader-following formation system. The traditional second-order sliding mode control is not perfect because the disturbances and uncertainties of the system may cause the compensation control to overestimate. The adaptive gain super-twisting sliding mode control suppresses the output oscillation and speeds up the system response by improving the gain function and adding a differential link. However, this method is generally applied to single-input single-output systems. This paper attempts to apply this method to a multi-input-multi-output leader-following formation system and improve its switching function and compensation control part. We use the estimators, i.e., the extreme learning machine and the nonlinear disturbance observer. These estimators can observe disturbance changes to replace the adaptive gain function to realise disturbance estimation and compensation control. Then combine the extreme learning machine and the nonlinear disturbance observer with the super-twisting sliding mode control to produce two new sliding mode methods. We use the Lyapunov method to prove the system stability as well. Finally, we illustrate the feasibility of the three control methods.

Keywords: multi-robot system; leader-following formation; sliding mode control; disturbance estimator.

DOI: 10.1504/IJAMECHS.2021.116487

International Journal of Advanced Mechatronic Systems, 2021 Vol.9 No.2, pp.85 - 101

Received: 09 Aug 2020
Accepted: 26 Apr 2021

Published online: 14 Jul 2021 *

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