报告题目：Unified Prescribed Performance Adaptive Control of Uncertain Systems

报告时间：2024年9月29日 19:00-20:00

主办单位：信息与人工智能学院、科技处

报告地点：线上（腾讯会议号：931808257）

报告人：

赵凯，重庆大学自动化学院教授，博导，自动化系主任，国家级青年人才，重庆英才青年人才项目。先后在澳大利亚纽卡斯尔大学、澳门大学和新加坡国立大学开展科研工作，主要从事非线性系统自适应约束控制、预设性能控制以及机器人系统研发和应用。主持国家自然科学基金项目1项，重庆英才青年拔尖人才项目1项，中央高校优秀青年团队项目1项，国家重点实验室开放课题1项，参与澳门特区和新加坡淡马锡实验室项目2项。出版中文专著1部，英文专著1部，发表SCI高水平论文35篇，包括控制理论国际顶级期刊IEEE Transactions on Automatic Control和Automatica 11篇，Google学术引用2100余次，ESI高被引论文6篇，热点论文1篇，授权发明专利2件。先后获得重庆大学（2020）、重庆市（2020）和中国自动化学会（2020）优秀博士学位论文奖（或提名奖）、IEEE Transactions on Cybernetics杰出审稿人（2022）、中国自动化学会科技进步一等奖（2023）等荣誉和称号。

报告内容：

This report presents an adaptive control method, capable of guaranteeing prescribed transient behavior for uncertain systems. Unlike most existing similar controls that are built upon time-varying feedback gains, the proposed method is derived from a tracking error/state-dependent function transformation, leading to a novel prescribed performance control solution with the following features: 1) by introducing an exponential transformation the corresponding control is able to achieve the exponential stabilization so that not only the persistent excitation condition is removed, but also the exponential convergence rate is independent of initial state; 2) by constructing a tracking error/state-dependent normalized function, with the aid of a series of function transformations, the proposed control is able to ensure different performance behaviors under a fixed control structure,without the requirements of control redesign and stability reanalysis. Both theoretical analysis and numerical simulations verify the effectiveness and benefits of the proposed method.