Adaptive Controller Design for Switched Stochastic Nonlinear Systems Subject to Unknown Dead-zone Input via New Type of Network Approach
摘要
In this article, adaptive tracking control for a class of switched stochastic nonlinear systems subject to unknown dead-zone input using multi-dimensional Taylor network (MTN) is studied. Firstly, the characteristic function is introduced to convert the nonlinearity of the input dead-zone into a linear model. Secondly, a novel adaptive control method based on the backstepping recursive design technique is proposed, which combines MTN and common Lyapunov functions (CLFs). Significantly, a method to reduce the computational complexity of switched stochastic nonlinear systems is proposed for the first time, which introduces characteristic function and MTN technology. The result makes clear that the proposed controller can ensure all signals of the closed-loop system are bounded in probability, and the output of the system can track reference signal well. Finally, the effectiveness of proposed control method is verified by simulation results.
类型
出版物
International Journal of Control, Automation and Systems
Form
Fuzzy Control
Global Stabilization
H-Infinity Control
Lyapunov Functions
Neural Tracking Control
Stability
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。
Authors
Authors