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Changhong Wang

Researcher at Harbin Institute of Technology

Publications -  87
Citations -  3693

Changhong Wang is an academic researcher from Harbin Institute of Technology. The author has contributed to research in topics: Linear matrix inequality & Convex optimization. The author has an hindex of 26, co-authored 78 publications receiving 3595 citations.

Papers
More filters
Journal ArticleDOI

A delay-dependent approach to robust H/sub /spl infin// filtering for uncertain discrete-time state-delayed systems

TL;DR: In this paper, a delay-dependent approach to robust H/sub/spl infin// filtering is proposed for linear discrete-time uncertain systems with multiple delays in the state.
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New approach to mixed H/sub 2//H/sub /spl infin// filtering for polytopic discrete-time systems

TL;DR: This paper revisits the problem of mixed H/sub 2//H/sub /spl infin// filtering for polytopic discrete-time systems and makes full use of the parameter-dependent stability idea, which results in a much less conservative filter design method.
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Delay-dependent robust H/sub /spl infin// and L/sub 2/-L/sub /spl infin// filtering for a class of uncertain nonlinear time-delay systems

TL;DR: In this paper, delay-dependent robust full-order and reduced-order filters for a class of nonlinear systems with multiple time-varying delays in the state and parameter uncertainties residing in a polytope are presented.
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Robust energy-to-peak filter design for stochastic time-delay systems

TL;DR: The most frequently used ways of dealing with parameter uncertainties, including polytopic and norm-bounded characterizations, have been taken into consideration, with convex optimization problems obtained for the design of desired robust energy-to-peak filters.
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Comments and further results on "A descriptor system approach to H/sub /spl infin// control of linear time-delay systems"

TL;DR: A new iterative state-feedback controller design procedure is proposed, based on a new bounded real lemma derived upon an inequality recently proposed by Moon (2001), which solves both the instantaneous and delayed feedback problems in a unified framework.