Adaptive Multi-Dimensional Taylor Network Tracking Control for a Class of Switched Nonlinear Systems with Input Nonlinearity
摘要
In this paper, a multi-dimensional Taylor network (MTN)-based adaptive tracking control approach is proposed for a class of switched nonlinear systems with input nonlinearity. Firstly, the input nonlinearity is assumed to be bounded by a sector interval. Secondly, with the help of MTNs approximating the unknown nonlinear functions, a novel adaptive MTN control scheme has the advantages of low cost, simple structure and real time feature is developed via backstepping technique. It is shown that the tracking error finally converges to a small domain around the origin and all signals in the closed-loop system are bounded. Finally, two examples are given to demonstrate the effectiveness of the proposed control scheme. © The Author(s) 2020.
类型
出版物
Transactions of the Institute of Measurement and Control
Adaptive Control Systems
Backstepping - Closed Loop Control Systems - Closed Loop Systems - Navigation
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。
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