学位:博士学位
学历:研究生(博士后)
职称:副教授
所在单位:自动化学院
学术荣誉: 曾获荣誉:
黄秀财,重庆万州人,重庆大学自动化学院副教授,硕士生导师,重庆大学自动化学院2013届学士、2018 届博士,美国密歇根州立大学联合培养博士,新加坡南洋理工大学博士后, 新重庆青年创新人才项目入选者。现任中国自动化学会可信控制专委会委员秘书长,自主无人系统安全与控制教育部国际合作联合实验室常务副主任。主要从事非线性控制理论,机器人及具身智能方面的研究,现已发表IEEE Trans会刊和IFAC汇刊文章30余篇,其中IEEE TAC和Automatica文章11篇,高被引论文1篇,受理/授权专利10余项,承担国家级/省部级纵向课题7项。成果先后获得中国自动化学会自然科学一等奖,教育部自然科学优秀成果二等奖,重庆大学、重庆市和中国电子学会优秀博士论文奖以及多个国际会议的最佳(提名)论文奖等。
Asymptotic tracking control of uncertain MIMO nonlinear systems with extended condition for controllability
所属单位:自动化学院
发表刊物:INTERNATIONAL JOURNAL OF ROBUST AND NONLINEAR CONTROL
关键字:Automation & Control Systems; Engineering, Electrical & Electronic; Mathematics, Applied
摘要:Most existing control methods for multi-input multioutput (MIMO) uncertain nonlinear systems can only achieve uniformly ultimately bounded stability with conservative controllability condition. In this note, for a larger class of uncertain MIMO strictfeedback nonlinear systems, we present a control solution with enhanced controllability condition by resorting to certain feasible auxiliary matrices, upon which a neural adaptive control scheme is developed that is able to achieve asymptotic tracking with guaranteed pre-assignable transient and steady-state performance in the presence of mismatched uncertainties and unknown yet timevarying control gain matrices, besides the semi-global ultimate uniform boundedness of the closed-loop signals. The salient feature of the proposed solution lies in its wider applicability and better control performance. Furthermore, the proposed solution does not involve any filter and the issue of the explosion of complexity is avoided. Numerical simulation also confirms the effectiveness of the proposed method.
第一作者:周炳
通讯作者:沈志熙
合写作者:黄秀财,周炳(学),SONG,YONG DUAN
论文类型:期刊论文
论文编号:261296
页面范围:-
ISSN号:1049-8923
是否译文:否
发表时间:2024-01-01
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