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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Finite-time stabilization of Markovian jump delay systems – a switching control approach
TL;DR: In this paper, a switching controller for a class of continuous-time Markovian jump delay systems (MJDSs) is proposed to make a trade-off between robustness and adaptiveness when the design complexity of mode-independent, mode-dependent, and modedependent and variation-dependent control strategies is considered.
Fuzzy risk analysis based on linguistic aggregation operators
Zheng Pei,Peng Shi +1 more
TL;DR: A new method for fuzzy risk analysis with linguistic evaluating values that has no need of approximation processing, no loss of information and no complex computation due to the linguistic aggregation operator and the 2-tuple fuzzy linguistic representations is presented.
Fault accommodation for near space vehicle attitude dynamics via T-S fuzzy models
TL;DR: Based on both adaptive and sliding mode control techniques, an integrated approach to fault detection, estimation and fault-tolerant control for near space vehicle (NSV) attitude dynamics during re-entry phase was proposed in this article.
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ℋ ∞ model reduction for linear parameter-varying systems with distributed delay
TL;DR: A sufficient condition is proposed for the asymptotic stability with an ℋ∞ performance of the error system by using the parameter-dependent Lyapunov functional method and two different approaches are developed to solve the model reduction problem.
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Fuzzy $n$ -Ellipsoid Numbers and Representations of Uncertain Multichannel Digital Information
TL;DR: This paper establishes an algorithmic version of constructing fuzzy n-ellipsoid numbers to express an object that is characterized by a group of uncertain multichannel digital information, as well as give practical examples to show the application and rationality of the proposed techniques.