报告题目：Input-to-StateStability of Discrete-Time Time-Varying Switched Delayed Systems

报告人：彭世国 教授/广东工业大学

报告时间：2019年10月28日(周一)上午 9:30

报告地点：电气楼308

报告对象：电气学院相关专业本科生、研究生、教师

主办单位：beat365

报告人简介：    

彭世国：广东工业大学自动化学院教授，博士生导师。1989年本科毕业于湘潭大学数学系，分别于1992、1995年获中山大学数学专业硕士学位和博士学位，2004年晋升为教授。近年来主要从事非线性时滞系统的稳定与控制、随机系统的稳定与控制等方面的研究。在IEEE-TAC、IEEE-TFS、SCL、JFI、 IET-CTA、JMAA、NA-RWA、NA-TMA、SPL、AJC、IEEE-ACCESS、IJSS、数学年刊、应用数学学报、系统科学与数学、数学物理学报等期刊发表论文80余篇，其中SCI论文30余篇，ESI高被引1篇，单篇SCI他引80余次。承担或参与多项国家自然科学基金项目、广东省自然科学基金自由申请项目及广东省自然科学基金团队项目的研究。

报告摘要：

In this paper, we are concerned with theproblem on input-to-state stability (ISS) for discrete-time time-varyingswitched delayed systems. Some Krasovskii and Razumikhin ISS criteria areprovided by using the notions of uniformly asymptotically stable (UAS) functionand mode-dependent average dwell time (MDADT).  With the help of theconcept of UAS function, the advantage of our results in this paper is that thecoefficients of the first order difference inequalities for the mode-dependentKrasovskii functionals and mode-dependent Razumkhin functions are allowed to betime-varying, mode-dependent, and can even take both positive and negativevalues, and the whole switched system can be allowed to have both ISSsubsystems and non-ISS subsystems. With the aid of the notion of MDADT, eachsubsystem can have its own average dwell time.  As an application, we alsoprovide an ISS criterion for discrete-time time-varying switched delayed Hopfieldneural networks with disturbance inputs. Numerical simulations verify theeffectiveness of the established criteria.