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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Adaptive Neural Dynamic Surface Control for Nonstrict-Feedback Systems With Output Dead Zone
TL;DR: A Nussbaum-type function-based dead-zone model is introduced such that the dynamic surface control approach can be used for controller design and it is rigorously shown that the proposed output-constrained controller guarantees that all the closed-loop signals are semiglobal uniformly ultimately bounded and the tracking error never violates the output constraint.
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Input-to-State Stability of Switched Nonlinear Systems With Time Delays Under Asynchronous Switching
TL;DR: An efficient condition is established, in terms of an upper bound on the switching delay, and a lowerbound on the matched time intervals for the subsystem and the controller, which ensures ISS for the whole switched nonlinear system.
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System Identification and Robust Control of Multi-Input Multi-Output Active Magnetic Bearing Systems
TL;DR: It is shown that the accurate modeling of the system being controlled is the key to the successful design of high-performance stable controllers that not only guarantee the internal stability of theSystem-controller interconnection but also that no further modifications are required before the real-time implementation of the designed controllers.
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Optimal Filtered and Smoothed Estimators for Discrete-Time Linear Systems With Multiple Packet Dropouts Under Markovian Communication Constraints
TL;DR: This paper design Kalman-like estimators in a recursive form for networked linear stochastic systems by means of the innovation analysis approach and orthogonal projection principle, and verifies the effectiveness and superiority of the designed algorithm.
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Adaptive Fault Diagnosis for T–S Fuzzy Systems With Sensor Faults and System Performance Analysis
Qikun Shen,Bin Jiang,Peng Shi +2 more
TL;DR: The analysis of the system performance degraded by TDDTFD is developed, and the conditions under which the magnitudes of sensor faults should be satisfied such that the state of the faulty system controlled by the normal controller remains bounded during TDD TFD are derived.