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Model predictive control of distributed networked control systems with quantization and switching topology
Author(s) -
Shi Ting,
Shi Peng,
Zhang Huiyan
Publication year - 2020
Publication title -
international journal of robust and nonlinear control
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.361
H-Index - 106
eISSN - 1099-1239
pISSN - 1049-8923
DOI - 10.1002/rnc.5002
Subject(s) - control theory (sociology) , model predictive control , quantization (signal processing) , upper and lower bounds , computer science , topology (electrical circuits) , control system , quadratic equation , mathematics , control (management) , engineering , algorithm , mathematical analysis , combinatorics , artificial intelligence , electrical engineering , geometry
Summary This work is concerned with the robust model predictive control (MPC) for a class of distributed networked control systems (NCSs), in which the input quantization and switching topology are both considered. By utilizing the sector bound approach, the NCSs with quantization are converted into the linear systems with sector bound uncertainties. The topology switching is governed by a switching signal and the dynamic behavior is modeled as a switched control system. A new robust MPC design technique is derived to minimize the upper bound of a weighted quadratic performance index. Moreover, the conditions of both the recursive feasibility of the MPC design and the stability of the resulting closed‐loop system are developed. Finally, simulation results are presented to verify the effectiveness of the proposed MPC design.