SPEAKER:            Jie Chen, City University of Hong Kong
TITLE:                   When is a Time-Delay System Stable and Stabilizable? A Third-Eye View
DATE & TIME:       September 15, 2023, Friday @ 4:00 pm (CET), 7:00 am (PDT), 10:00 am (EDT), 10:00 pm (CST)
REGISTRATION:  https://umich.zoom.us/meeting/register/tJAqdeGvrDsoHdMrJUvUS90pAk4in3FpAwC5
                             The registration is free and takes about 30 seconds. If you experience any issues please email orosz@umich.edu

ABSTRACT: Time delays are a prevailing scene in natural and engineered systems. While a recurring subject in classical studies, modern interconnected networks are especially prone and indeed, are vulnerable to long and variable delays; systems and networks in this category are many, ranging from communication networks, sensor networks, cyber-physical systems, to biological systems. A time-delay system may or may not be stable for different lengths of delay, and further, may or may not be stabilized under a conventional feedback mechanism. When will then a delay system be stable or unstable, and for what values of delay? When can an unstable delay system be stabilized? What range of delay can a feedback system tolerate to maintain stability? Fundamental questions of this kind have long eluded engineers and mathematicians alike, yet ceaselessly invite new thoughts and solutions. In this talk I shall present a nontraditional perspective on the stability and stabilization of time-delay systems, wherein we attempt to develop tools and techniques that answer to the questions alluded to above, seeking to provide exact and efficient computational solutions to stability and stabilization problems of time-delay systems. We develop in full an operator-theoretic approach that departs from both the classical algebraic and the omnipresent LMI solution approaches, notable for both its conceptual appeal and its computational efficiency. Preceding this development we shall also develop the necessary mathematical foundation centered at operator perturbation series, which characterize the analytical and asymptotic properties of eigenvalues of matrix-valued functions or operators. Extensions to contemporary topics such as networked control and multi-agent systems may also be addressed.
--
FROM 124.14.44.*