Iterative Learning Tracking Control of Nonlinear Multiagent Systems with Input Saturation. (11th March 2021)

• Record Type: Journal Article
• Authors: Liu, Bingyou; Zhang, Zhengzheng; Wang, Lichao; Li, Xing; Deng, Xiongfeng
• Other Names: Pratama Mahardhika Academic Editor.
• Is Part Of: Complexity. Volume 2021(2021)
• Publication Date: 2021-03-11
• Subjects: Chaotic behavior in systems -- Periodicals; Complexity (Philosophy) -- Periodicals; 003
• DOI: 10.1155/2021/2940218
• Languages: English
• ISSNs: 1076-2787

Abstract

Abstract : A tracking control algorithm of nonlinear multiple agents with undirected communication is studied for each multiagent system affected by external interference and input saturation. A control design scheme combining iterative learning and adaptive control is proposed to perform parameter adaptive time-varying adjustment and prove the effectiveness of the control protocol by designing Lyapunov functions. Simulation results show that the high-precision tracking control problem of the nonlinear multiagent system based on adaptive iterative learning control can be well realized even when the input is saturated. Finally, the validity of the proposed algorithm is verified by numerical analysis.