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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Networked Control Systems: The Communication Basics and Control Methodologies
TL;DR: The basics of networked control systems are introduced and the state-of-the-art research in this field is described, in the hope this brief tutorial can be useful to inspire further development of networking control systems in both theory and potential applications.
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Effects of Additives on the Morphology of Thiamine Nitrate: The Great Difference of Two Kinds of Similar Additives
Dandan Han,Bo Yu,Yumin Liu,Shichao Du,Sohrab Rohani,Teng Zhang,Shiyuan Liu,Peng Shi,Haisheng Wang,Lina Zhou,Junbo Gong +10 more
TL;DR: In this paper, the growth of the a-axis of thiamine nitrate is significantly inhibited by CH3(CH2)nSO4Na, thus reducing the aspect ratio.
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Robust adaptive sliding mode control for uncertain delta operator systems
TL;DR: In this article, a robust adaptive sliding mode controller for delta operator systems with mismatched uncertainties and exogenous disturbances is presented, where the parameters of the delta operator system are taken for norm-bounded uncertainties and the exogenous disturbance is also assumed to be bounded.
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Thermodynamic study of solubility for pyrazinamide in ten solvents from T = (283.15 to 323.15) K
Keke Zhang,Huan Shen,Shijie Xu,Huihui Zhang,Zhu Minghe,Peng Shi,Xiaoyan Fu,Yaoyao Yang,Junbo Gong +8 more
TL;DR: In this paper, the experimental results indicated that in different solvents, the solubility of pyrazinamide was temperature dependent and increased with the increasing temperature, and the modified Apelblat equation, λh equation, Wilson model and NRTL model were employed to correlate the data.
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Fuzzy model-based asynchronous H∞ filter design of discrete-time Markov jump systems
TL;DR: Two totally different but equivalent methods are adopted to derive sufficient conditions that ensure stochastic stability as well as a prescribed H∞ performance of the filtering error system.