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Open AccessArticle

Second-Order Sliding Mode Formation Control of Multiple Robots by Extreme Learning Machine

1
School of Control and Computer Engineering, North China Electric Power University, Beijing 102206, China
2
Institute of Automation, Chinese Academy of Sciences, Beijing 100190, China
3
Institute of Mechanical and Electrical Engineering, Shenzhen Polytechnic, Shenzhen 518055, China
*
Author to whom correspondence should be addressed.
Symmetry 2019, 11(12), 1444; https://doi.org/10.3390/sym11121444
Received: 7 October 2019 / Revised: 21 November 2019 / Accepted: 21 November 2019 / Published: 23 November 2019
(This article belongs to the Special Issue Asymptotic Methods in the Mechanics and Nonlinear Dynamics)
This paper addresses a second-order sliding mode control method for the formation problem of multirobot systems. The formation patterns are usually symmetrical. This sliding mode control is based on the super-twisting law. In many real-world applications, the robots suffer from a great diversity of uncertainties and disturbances that greatly challenge super-twisting sliding mode formation maneuvers. In particular, such a challenge has adverse effects on the formation performance when the uncertainties and disturbances have an unknown bound. This paper focuses on this issue and utilizes the technique of an extreme learning machine to meet this challenge. Within the leader–follower framework, this paper investigates the integration of the super-twisting sliding mode control method and the extreme learning machine. The output weights of this extreme learning machine are adaptively adjusted so that this integrated formation design has guaranteed closed-loop stability in the sense of Lyaponov. In the end, some simulations are implemented via a multirobot platform, illustrating the superiority and effectiveness of the integrated formation design in spite of uncertainties and disturbances.
Keywords: multirobot systems; formation maneuvers; super-twisting sliding mode control; uncertainties; extreme learning machine multirobot systems; formation maneuvers; super-twisting sliding mode control; uncertainties; extreme learning machine
MDPI and ACS Style

Qian, D.; Zhang, G.; Wang, J.; Wu, Z. Second-Order Sliding Mode Formation Control of Multiple Robots by Extreme Learning Machine. Symmetry 2019, 11, 1444.

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