学术报告                                                                                                                                                                                                        

报告题目：Adaptive Neural Tracking Control for Uncertain       

Switched Nonlinear Non-lower Triangular System  

with Disturbances and Dead-zone Input    

报 告 人：李睿兵 博士(哈尔滨工程大学)    

报告时间：2021年5月13日(星期四 ) 17:30               

报告地点：信息大厦B808教室    

主办单位：研究生学院、数学与计算机科学学院  

报告主要内容：This work investigates the adaptive neural tracking control problem for a class of uncertain switched nonlinear non-lower triangular systems with disturbances and dead-zone input. Radial basis function neural networks serve as a flexible tool to approximate the unknown nonlinear functions. Then during the controller design, the dynamic surface control method is used to avoid the issue of "explosion of complexity", and only one adaptive law is adopted to reduce the computational burden. What’s more, a few classical mathematical approaches are used to handle the design difficulties caused by dead-zone input, and the proposed controller guarantees the closed-loop system signals are semi-globally uniform ultimate boundedness.    

报告人简介：李睿兵，哈尔滨工程大学智能科学与工程学院，博士在读。主要从事智能算法、切换系统、随机非线性系统以及自适应智能控制等方面的研究工作。在国际控制领域主要学术期刊及会议上发表论文5篇，获山东省研究生优秀成果二等奖。    

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