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Gradient‐based optimization techniques for the design of static controllers for Markov jump linear systems with unobservable modes
Author(s) -
Vargas Alessandro N.,
Bortolin Daiane C.,
Costa Eduardo F.,
Val João B.R.
Publication year - 2014
Publication title -
international journal of numerical modelling: electronic networks, devices and fields
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.249
H-Index - 30
eISSN - 1099-1204
pISSN - 0894-3370
DOI - 10.1002/jnm.1981
Subject(s) - unobservable , jump , markov chain , control theory (sociology) , markov process , computer science , mathematical optimization , mathematics , control (management) , physics , econometrics , statistics , artificial intelligence , quantum mechanics
Summary The paper formulates the static control problem of Markov jump linear systems, assuming that the controller does not have access to the jump variable. We derive the expression of the gradient for the cost motivated by the evaluation of 10 gradient‐based optimization techniques. The numerical efficiency of these techniques is verified by using the data obtained from practical experiments. The corresponding solution is used to design a scheme to control the velocity of a real‐time DC motor device subject to abrupt power failures. Copyright © 2014 John Wiley & Sons, Ltd.