Distributed consensus tracking for non-linear multi-agent systems with input saturation: a command filtered backstepping approach

• Published in: IET control theory & applications Vol. 10; no. 5; pp. 509 - 516
• Main Authors: Cui, Guozeng, Xu, Shengyuan, L. Lewis, Frank, Zhang, Baoyong, Ma, Qian
• Format: Journal Article
• Language: English
• Published: The Institution of Engineering and Technology 21.03.2016
• Subjects: auxiliary system; backstepping design framework; closed loop systems; command filtered backstepping approach; Commands; compensation; Computer simulation; consensus tracking errors; control design; control nonlinearities; control system synthesis; Design engineering; design parameters tuning; directed graphs; distributed consensus control scheme; distributed consensus tracking problem; distributed control; feedback; fixed directed graph; followers dynamics; input saturation; Lyapunov methods; Lyapunov stability theory; Multiagent systems; multi‐agent systems; Neural networks; neurocontrollers; Nonlinear dynamics; nonlinear functions; nonlinear multiagent systems; Nonlinearity; Saturation; semiglobally uniformly ultimately bounded; stability; strict‐feedback structures; unknown nonlinear functions; unknown nonlinearities; distributed consensus tracking problem; multi-agent systems; nonlinear functions; neural networks; followers dynamics; unknown nonlinear functions; feedback; command filtered backstepping approach; design parameters tuning; neurocontrollers; auxiliary system; control nonlinearities; Lyapunov stability theory; stability; strict-feedback structures; unknown nonlinearities; distributed control; control system synthesis; semiglobally uniformly ultimately bounded; nonlinear multiagent systems; fixed directed graph; closed loop systems; distributed consensus control scheme; directed graphs; input saturation; consensus tracking errors; compensation; control design; closed-loop systems; Lyapunov methods; backstepping design framework
• ISSN: 1751-8644; 1751-8652
• DOI: 10.1049/iet-cta.2015.0627

This study deals with the distributed consensus tracking problem for non-linear multi-agent systems under a fixed directed graph. The dynamics of the followers are taken as strict-feedback structures with unknown non-linearities and input saturation. Neural networks are utilised to identify a certain scalar related to the unknown non-linear functions, and an auxiliary system is introduced into the control design to compensate the effect of input saturation. By incorporating the command filtered technique into the backstepping design framework, a distributed consensus control scheme is constructed recursively. Using the Lyapunov stability theory, it is proved that all signals in the closed-loop systems are cooperatively semi-globally uniformly ultimately bounded and the consensus tracking errors converge to a small neighbourhood of origin by tuning the design parameters. Finally, simulation result demonstrates the effectiveness of the proposed control approach.