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Performance analysis of networked predictive control systems with data dropout
Author(s) -
Xia Yuanqing,
Xie Wen,
Zhu Zheng,
Wang Ge,
Wang Xiaoyun
Publication year - 2012
Publication title -
optimal control applications and methods
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.458
H-Index - 44
eISSN - 1099-1514
pISSN - 0143-2087
DOI - 10.1002/oca.2056
Subject(s) - dropout (neural networks) , networked control system , computer science , model predictive control , control (management) , scheme (mathematics) , generator (circuit theory) , control system , control theory (sociology) , data transmission , transmission (telecommunications) , control engineering , engineering , machine learning , computer network , artificial intelligence , power (physics) , mathematics , telecommunications , mathematical analysis , physics , quantum mechanics , electrical engineering
SUMMARY This paper is concerned with the design of networked control systems with random network data dropout. It presents a new control scheme, which is termed networked predictive control. This scheme mainly consists of the control prediction generator and network data dropout compensator. Besides, the control prediction generator provides a set of future control predictions to make the closed‐loop system achieve the desired control performance, and the network data dropout compensator removes the effects of the network transmission data dropout. Simulation results are presented to illustrate the effectiveness of the control strategy via comparing with other three existing control schemes. Copyright © 2012 John Wiley & Sons, Ltd.