Control Design for Stochastic Nonlinear Systems with Full-state Constraints and Input Delay: A New Adaptive Approximation Method
摘要
In this paper, the full state constraints and input delay of stochastic nonlinear systems are studied. A new adaptive control algorithm is proposed using backstepping approach and multi-dimensional Taylor network (MTN) method. Firstly, the input delay problem is dealt with by introducing a new iable using the Pade approximation with Laplace transform. Secondly, MTNs are employed to approximate unknown nonlinear functions, and the barrier Lyapunov functions (BLFs) are constructed to deal with the state constraints. Based on this, a new approximation-based adaptive controller is proposed. Thirdly, it is proved that the proposed control method can ensure that all signals in the closed-loop system are semi-global ultimately uniformly bounded (SGUUB) in probability and the tracking error converges to a small neighborhood of the origin. Finally, two simulation examples are given to illustrate the effectiveness of the proposed design method.
类型
出版物
International Journal of Control, Automation and Systems
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。