J
Jun Zhao
Researcher at Northeastern University (China)
Publications - 430
Citations - 11334
Jun Zhao is an academic researcher from Northeastern University (China). The author has contributed to research in topics: Lyapunov function & Nonlinear system. The author has an hindex of 44, co-authored 407 publications receiving 9610 citations. Previous affiliations of Jun Zhao include Northeastern University & City University of Hong Kong.
Papers
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Stability and L2-gain analysis for switched delay systems: A delay-dependent method
TL;DR: Sufficient conditions for exponential stability and weighted L"2-gain are developed for a class of switching signals with average dwell time and these conditions are given in the form of linear matrix inequalities (LMIs).
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On stability, L2-gain and H∞ control for switched systems
Jun Zhao,David J. Hill +1 more
TL;DR: In this article, a necessary and sufficient condition for stability of switched systems is given in terms of multiple generalized Lyapunov-like functions, which enables derivation of improved stability tests, an L"2-gain characterization and a design method for stabilizing switching laws.
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Dissipativity Theory for Switched Systems
Jun Zhao,David J. Hill +1 more
TL;DR: A frame work of dissipativity theory for switched systems using multiple storage functions and multiple supply rates is set up, and asymptotic stability is guaranteed under certain "negative" output feedback.
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Brief paper: Backstepping design for global stabilization of switched nonlinear systems in lower triangular form under arbitrary switchings
Ruicheng Ma,Jun Zhao +1 more
TL;DR: Two classes of state feedback controllers and a common Lyapunov function (CLF) are simultaneously constructed by backstepping to solve the global stabilization problem for switched nonlinear systems in lower triangular form under arbitrary switchings.
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Barrier Lyapunov functions for the output tracking control of constrained nonlinear switched systems
TL;DR: A continuous feedback controller is designed for the switched system, which guarantees that asymptotic output tracking is achieved without transgression of the constraints and all closed-loop signals remain bounded, provided that the initial states are feasible.