Observer-based robust adaptive neural control for nonlinear multi-agent systems with quantised input

Xing-Yu Zhang, Yuan-Xin Li and Jiaxu Sun

International Journal of Systems Science, 2024, vol. 55, issue 6, 1270-1282

Abstract: This article discusses the issue of robust adaptive neural network (NN) consensus tracking control for nonlinear strict-feedback multi-agent systems with quantised input. By combining the neural network approach with robust techniques, a novel switching function is introduced to guarantee the tracking performance of this system. To estimate the unmeasured state, an NN-based adaptive state observer is developed. Based on backstepping dynamic surface control algorithms, a robust output feedback controller is constructed to guarantee that all signals in the closed-loop system remain globally uniformly ultimately bounded. Finally, numerical simulations are carried out to demonstrate the effectiveness of the presented algorithm.

Date: 2024
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DOI: 10.1080/00207721.2024.2304133

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