Adaptive Decentralized Control for Large‐scale Nonlinear Systems with Finite‐time Output Constraints by Multi‐ Dimensional Taylor Network
摘要
This paper investigates the adaptive decentralized control problem for a class of large-scale nonlinear systems with finite-time output constraints. In order to ensure that the tracking errors are constrained within a predefined in finite time, a novel adaptive barrier Lyapunov function (BLF) control method is proposed by combining the modified finite-time performance function (FTPF) in the first step of backstepping process. Besides, the mean value theorem and regulating functions are employed to handle the difficulties caused by interconnection functions in large-scale systems. Subsequently, with the approximation performance of multi-dimensional Taylor network (MTN), a MTN-based adaptive decentralized tracking control scheme is developed to guarantee that the tracking errors satisfy the prescribed performance and all signals of the closed-loop systems are bounded. Finally, the stability theory analysis and simulation results demonstrate the effectiveness of the proposed method.
类型
出版物
Asian Journal of Control
Authors
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。