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Robust Model Predictive Control with One Free Control Move for NCSs with Data Missing

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International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Year of Publication: 2016
Authors:
Jimin Yu, Xiaogang Gong
10.5120/ijca2016911825

Jimin Yu and Xiaogang Gong. Robust Model Predictive Control with One Free Control Move for NCSs with Data Missing. International Journal of Computer Applications 152(3):1-8, October 2016. BibTeX

@article{10.5120/ijca2016911825,
	author = {Jimin Yu and Xiaogang Gong},
	title = {Robust Model Predictive Control with One Free Control Move for NCSs with Data Missing},
	journal = {International Journal of Computer Applications},
	issue_date = {October 2016},
	volume = {152},
	number = {3},
	month = {Oct},
	year = {2016},
	issn = {0975-8887},
	pages = {1-8},
	numpages = {8},
	url = {http://www.ijcaonline.org/archives/volume152/number3/26296-2016911825},
	doi = {10.5120/ijca2016911825},
	publisher = {Foundation of Computer Science (FCS), NY, USA},
	address = {New York, USA}
}

Abstract

Current hot issue of networked control systems(NCSs) remains how to optimize the signal transmission in imperfect links, especially, data missing(between the controller and actuator) is a potential source of poor performance of the control system. Here, stochastic variables satisfying markov jump process are used to describe the fading channel. Considering the uncertainty factor of plant, a practical compensation technique is utilized to minimize the effects caused by data dropout. Attention is paid to designing a useful control law to drive the closed-loop system stable and preserve a guaranteed infinite-horizon performance function, where the infinite-horizon control moves are parameterized as a free control move. Furthermore, the corresponding problems about recursive feasibility and stochastic stability are established by a set of linear matrix inequalities. Simulation results are shown to verify the performance of the proposed approach.

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Keywords

Data missing, polytoic model, state feedback