Neural network sliding mode control of multi-agent systems based on a preview mechanism and whale optimization algorithm

作     者：Chen, Yuxin Ren, Junchao 

作者机构：Northeastern Univ Coll Sci 3-11 Wenhua Rd Shenyang 110819 Liaoniong Peoples R China 

出 版 物：《PROCEEDINGS OF THE INSTITUTION OF MECHANICAL ENGINEERS PART I-JOURNAL OF SYSTEMS AND CONTROL ENGINEERING》 (Proc Inst Mech Eng Part I J Syst Control Eng)

年 卷 期：2025年第239卷第5期

页      面：823-840页

核心收录：

学科分类：08[工学] 0802[工学-机械工程] 0811[工学-控制科学与工程] 

基　　金：National Natural Science Foundation of China Fundamental Research Funds for the Central Universities [N2224005-2, N150504011] 

主　　题：Preview mechanism sliding mode control multi-agent systems neural network whale optimization algorithm 

摘      要：In this work, a neural network sliding mode control (SMC) scheme is proposed to address the tracking issue of discrete-time multi-agent systems (MASs) with unknown nonlinearities by combining the preview mechanism and whale optimization algorithm. An augmented error system (AES) was constructed, which includes previewable reference and disturbance signals. A new sliding mode surface is designed for AES, and the stability criteria are proposed for the sliding mode dynamics. Utilizing the preview mechanism and whale optimization algorithm, the neural network-based SMC law is designed to satisfy the discrete-time reachability condition. Two simulation examples are provided to demonstrate that the proposed control scheme can effectively enhance the tracking performance of MASs.