P
Peng Shi
Researcher at University of Adelaide
Publications - 1601
Citations - 80441
Peng Shi is an academic researcher from University of Adelaide. The author has contributed to research in topics: Control theory & Nonlinear system. The author has an hindex of 137, co-authored 1371 publications receiving 65195 citations. Previous affiliations of Peng Shi include Harbin Engineering University & Harbin University of Science and Technology.
Papers
More filters
Journal ArticleDOI
A novel approach to output feedback control of fuzzy stochastic systems
TL;DR: This paper investigates the problem of Hankel-norm output feedback controller design for a class of T-S fuzzy stochastic systems and proposes the fuzzy-basis-dependent Lyapunov function approach and the conversion on theHankel- norm controller parameters.
Journal ArticleDOI
Adaptive Neural Control for a Class of Perturbed Strict-Feedback Nonlinear Time-Delay Systems
Min Wang,Bing Chen,Peng Shi +2 more
TL;DR: A novel adaptive neural control scheme for a class of perturbed strict-feedback nonlinear time-delay systems with unknown virtual control coefficients is presented by combining the backstepping approach and Lyapunov-Krasovskii functionals.
Journal ArticleDOI
Consensus Tracking Control of Switched Stochastic Nonlinear Multiagent Systems via Event-Triggered Strategy
TL;DR: In this paper, the consensus tracking problem is investigated for a class of continuous switched stochastic nonlinear multiagent systems with an event-triggered control strategy and a new protocol design framework is proposed for the underlying systems.
Journal ArticleDOI
Fault Detection Filtering for Nonhomogeneous Markovian Jump Systems via a Fuzzy Approach
TL;DR: This paper investigates the problem of the fault detection filter design for nonhomogeneous Markovian jump systems by a Takagi–Sugeno fuzzy approach to ensure the estimation error dynamic stochastically stable, and the prescribed performance requirement can be satisfied.
Journal ArticleDOI
Sensor Networks With Random Link Failures: Distributed Filtering for T–S Fuzzy Systems
Xiaojie Su,Ligang Wu,Peng Shi +2 more
TL;DR: Sufficient conditions for the obtained filtering error dynamic system are proposed by applying an comparison model and the scaled small gain theorem and the solution of the parameters of the distributed fuzzy filters is characterized in terms of the feasibility of a convex optimization problem.