Robust bipartite tracking consensus of multi-agent systems via neural network combined with extended high-gain observer

Weihao Li; Kaiyu Qin; Gun Li; Mengji Shi; Xinyu Zhang

doi:10.1016/j.isatra.2022.10.015

Robust bipartite tracking consensus of multi-agent systems via neural network combined with extended high-gain observer

ISA Trans. 2023 May:136:31-45. doi: 10.1016/j.isatra.2022.10.015. Epub 2022 Oct 26.

Authors

Weihao Li¹, Kaiyu Qin², Gun Li³, Mengji Shi⁴, Xinyu Zhang⁵

Affiliations

¹ School of Aeronautics and Astronautics, University of Electronic Science and Technology of China, Chengdu, 611731, China; Aircraft Swarm Intelligent Sensing and Cooperative Control Key Laboratory of Sichuan Province, Chengdu, 611731, China. Electronic address: liweihao@std.uestc.edu.cn.
² School of Aeronautics and Astronautics, University of Electronic Science and Technology of China, Chengdu, 611731, China; Aircraft Swarm Intelligent Sensing and Cooperative Control Key Laboratory of Sichuan Province, Chengdu, 611731, China. Electronic address: kyqin@uestc.edu.cn.
³ School of Aeronautics and Astronautics, University of Electronic Science and Technology of China, Chengdu, 611731, China; Aircraft Swarm Intelligent Sensing and Cooperative Control Key Laboratory of Sichuan Province, Chengdu, 611731, China. Electronic address: ligun@uestc.edu.cn.
⁴ School of Aeronautics and Astronautics, University of Electronic Science and Technology of China, Chengdu, 611731, China; Aircraft Swarm Intelligent Sensing and Cooperative Control Key Laboratory of Sichuan Province, Chengdu, 611731, China. Electronic address: maangat@126.com.
⁵ School of Aeronautics and Astronautics, University of Electronic Science and Technology of China, Chengdu, 611731, China; Aircraft Swarm Intelligent Sensing and Cooperative Control Key Laboratory of Sichuan Province, Chengdu, 611731, China; School of Computer Science and Engineering, University of Electronic Science and Technology of China, Chengdu, 611731, China. Electronic address: xyu_zhang@hotmail.com.

PMID: 36344356
DOI: 10.1016/j.isatra.2022.10.015

Abstract

In this paper, the robust bipartite tracking consensus problem for second-order multi-agent systems has been addressed in the presence of lumped disturbances and unknown velocity information. The leader's dynamics are modeled by uncertain fractional-order equality based on the neural network (NN), and the followers can only obtain the position information of the leader under the signed networks. A novel robust bipartite tracking consensus control scheme is developed by combining the NN approximators, the continuous sliding mode control (SMC) strategy, and the improved extended high-gain observer (EHGO). The improved EHGO is used to compensate for and estimate each agent's lumped disturbances and unknown velocity information in the controller design process. Moreover, NN is constructed to approximate the velocity and acceleration of the uncertain leader's dynamics for generating the feedforward signal of controllers, and the adaptive update laws of estimation parameters are generated online based on the Lyapunov function. Finally, the effectiveness of the proposed control strategy is verified by some numerical simulations.

Keywords: Bipartite tracking consensus; Extended high-gain observer; Neural network; Sliding mode control; Without velocity measurements.