Adaptive Multi‐dimensional Taylor Network Tracking Control for Nonlinear Systems with Input Saturation and~Full~State Time‐varying Constraints
摘要
In this article, an adaptive multi-dimensional Taylor network (MTN) control approach is developed for nonlinear systems subject to input saturation and full state time-ying constraints. Using the function approximation property of MTN, an adaptive tracking control method is developed by incorporating the concept of time-ying state constraints into the construct of barrier Lyapunov functions. The proposed approach not only ensures all closed-loop system signals are bounded but also that all states of the system never violate the given time-ying constraints. The most important advantage of the proposed control strategy is that it can obtain satisfactory control effects with low computational cost. Finally, two examples are given to validate the effectiveness of the proposed method.
类型
出版物
International Journal of Adaptive Control and Signal Processing
Authors
Authors
Authors
Authors
正教授
教授，博士生导师，哈尔滨工业大学博士后。数据科学与信息技术研究中心主任，人工智能海洋技术场景化应用山东省工程研究中心主任，青岛市人工智能海洋技术创新中心主任，青岛科技大学数学与交叉研究院院长。美国佐治亚理工学院高级访问学者、香港中文大学高级访问学者、北京交通大学高级访问学者；山东省数学会常务理事、山东省应用统计学会常务理事、人工智能海洋学专业委员会常务委员。近年来，主持或参与国家自然科学基金、国防科工委、电子工业部、省自然基金、省重点科研计划、省高校科研计划、省优秀中青年科学家基金、青岛市科技发展计划项目等各级各类科研项目40多项。