Adaptive Decentralized Tracking Control for a Class of Large-Scale Nonlinear Systems with Dynamic Uncertainties Using Multi-dimensional Taylor Network Approach
摘要
For the large-scale nonlinear systems subject to dynamic uncertainties, an adaptive multi-dimensional Taylor network (MTN)-based decentralized control strategy is proposed, which can effectively solve output tracking control problem of the systems. Firstly, a dynamic signal is introduced to cope with the problem of unknown nonlinear dynamic uncertainties. Secondly, in each step of the backstepping, only one MTN is used to approximate the combination of unknown nonlinear functions. Then, in the last step of the backstepping, a new adaptive control scheme is designed, which realizes the stability and boundedness of the controlled systems. It is worth noting that the large-scale nonlinear systems, the unknown dynamic uncertainties and the MTN appear in the same framework for the first time. Finally, three simulation examples are presented to verify the feasibility of the proposed control strategy.
类型
出版物
Neural Processing Letters
Authors
Authors
Authors
Authors
正教授
博士，教授，硕士生导师，人工智能技术海洋场景化应用山东省工程研究中心副主任，青岛市人工智能海洋技术创新中心副主任，青岛科技大学数学与交叉研究院副院长。山东赛区数学建模竞赛专家组成员、山东省数学会理事、山东省应用统计学会理事、人工智能海洋学专业委员会委员。近年来，主持或参与国家自然科学基金、省自然基金、省教改项目等各类教学科研项目20多项，在国内外期刊发表学术论文80余篇，其中被SCI、EI检索70余篇，参编教材1部。指导学生参加全国大学生数学建模竞赛、中国研究生数学建模竞赛、美国大学生数学建模竞赛等各类竞赛获国家一等奖9项、国家二等奖29项、国家三等奖13项、山东省一等奖37项、山东省二等奖12项、山东省三等奖7项。指导本科生参加国家大学生创新计划项目4项。