Finite-Time Adaptive Fuzzy Prescribed Performance Formation Control for High-Order Nonlinear Multiagent Systems Based on Event-Triggered Mechanism

• Published in: IEEE transactions on fuzzy systems Vol. 31; no. 4; pp. 1229 - 1239
• Main Authors: Zhou, Haodong, Sui, Shuai, Tong, Shaocheng
• Format: Journal Article
• Language: English
• Published: New York IEEE 01.04.2023; The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
• Subjects: Adaptive control; Algorithms; Approximation algorithms; Artificial neural networks; Backstepping; Control methods; Control systems; Control theory; Dynamical systems; Event-triggered mechanism; finite-time; forma- tion control; Formation control; Fuzzy control; Fuzzy logic; Fuzzy systems; Heuristic algorithms; high-order nonlinear multiagent systems (MASs); Multiagent systems; Nonlinear control; Nonlinear dynamics; Nonlinear systems; prescribed performance; Tracking errors
• ISSN: 1063-6706; 1941-0034
• DOI: 10.1109/TFUZZ.2022.3197938

This article investigates the finite-time adaptive fuzzy prescribed performance formation control problem for high-order nonlinear multiagent systems. Fuzzy logic systems (FLSs) are adopted to approximate the unknown nonlinear dynamics. By combining the dynamic surface control technique and backstepping recursive design, an adaptive fuzzy prescribed performance formation control algorithm is developed. To reduce unnecessary transmission of network resources, a novel event-triggered mechanism is proposed in the control method. Subsequently, based on the adding power integral method and finite-time stability theory, it is proved that all signals of the controlled system are bounded and the tracking errors do not exceed the prescribed performance bounds in a finite time. Simulation results are given to verify that the presented formation control scheme achieves desired results.