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
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Sampled-Data Synchronization of Chaotic Lur'e Systems With Time Delays
TL;DR: This paper studies the problem of sampled-data control for master-slave synchronization schemes that consist of identical chaotic Lur'e systems with time delays with a novel Lyapunov functional, which is positive definite at sampling times but not necessarily positive definite inside the sampling intervals.
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Transition probability bounds for the stochastic stability robustness of continuous- and discrete-time Markovian jump linear systems
TL;DR: By using stochastic Lyapunov function approach and Kronecker product transformation techniques, sufficient conditions are obtained for the robust Stochastic stability of the underlying systems, which are in terms of upper bounds on the perturbed transition rates and probabilities.
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Stability of a class of switched positive linear time-delay systems
TL;DR: In this paper, the stability analysis of a class of switched positive linear time-delay systems with constant time delay was studied and a sufficient stability criterion was proposed for the underlying system under average dwell time switching.
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Adaptive Neural Tracking Control for a Class of Nonlinear Systems With Dynamic Uncertainties
TL;DR: A neural networks-based tracking control method is developed for uncertain nonlinear systems with unmodeled dynamics and nonlower triangular form and it is shown that the proposed controller is able to ensure the semi-global boundedness of all signals of the resulting closed-loop system.
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Fault Estimation and Tolerant Control for Fuzzy Stochastic Systems
Ming Liu,Xibin Cao,Peng Shi +2 more
TL;DR: A new robust observer technique is presented to obtain the estimates of the system states and the sensor faults simultaneously, and a fuzzy fault-tolerant control scheme is developed to guarantee the closed-loop system to be exponentially stable in mean square.