Predictive control of convex polyhedron LPV systems with Markov jumping parameters

The problem of receding horizon predictive control of stochastic linear parameter varying systems is discussed. First, constant coefficient matrices are obtained at each vertex in the interior of linear parameter varying system, and then, by considering semi-definite programming constraints, weight...

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Main Authors: Yin, YanYan, Liu, F., Shi, P., Karimi, H.
Other Authors: na
Format: Conference Paper
Published: IEEE 2012
Online Access:http://hdl.handle.net/20.500.11937/66246
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author Yin, YanYan
Liu, F.
Shi, P.
Karimi, H.
author2 na
author_facet na
Yin, YanYan
Liu, F.
Shi, P.
Karimi, H.
author_sort Yin, YanYan
building Curtin Institutional Repository
collection Online Access
description The problem of receding horizon predictive control of stochastic linear parameter varying systems is discussed. First, constant coefficient matrices are obtained at each vertex in the interior of linear parameter varying system, and then, by considering semi-definite programming constraints, weight coefficients between each vertex are calculated, and the equal coefficients matrices for the time variable system are obtained. Second, in the given receding horizon, for each mode sequence of the stochastic convex polyhedron linear parameter varying systems, the optimal control input sequences are designed in order to make the states into a terminal invariant set. Outside of the receding horizon, stability of the system is guaranteed by searching a state feedback control law. Finally, receding horizon predictive controller is designed in terms of linear matrix inequality for such system. Simulation example shows the validity of this method. © 2012 IEEE.
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institution Curtin University Malaysia
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publishDate 2012
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spelling curtin-20.500.11937-662462018-04-30T02:48:32Z Predictive control of convex polyhedron LPV systems with Markov jumping parameters Yin, YanYan Liu, F. Shi, P. Karimi, H. na The problem of receding horizon predictive control of stochastic linear parameter varying systems is discussed. First, constant coefficient matrices are obtained at each vertex in the interior of linear parameter varying system, and then, by considering semi-definite programming constraints, weight coefficients between each vertex are calculated, and the equal coefficients matrices for the time variable system are obtained. Second, in the given receding horizon, for each mode sequence of the stochastic convex polyhedron linear parameter varying systems, the optimal control input sequences are designed in order to make the states into a terminal invariant set. Outside of the receding horizon, stability of the system is guaranteed by searching a state feedback control law. Finally, receding horizon predictive controller is designed in terms of linear matrix inequality for such system. Simulation example shows the validity of this method. © 2012 IEEE. 2012 Conference Paper http://hdl.handle.net/20.500.11937/66246 10.1109/CCDC.2012.6244093 IEEE restricted
spellingShingle Yin, YanYan
Liu, F.
Shi, P.
Karimi, H.
Predictive control of convex polyhedron LPV systems with Markov jumping parameters
title Predictive control of convex polyhedron LPV systems with Markov jumping parameters
title_full Predictive control of convex polyhedron LPV systems with Markov jumping parameters
title_fullStr Predictive control of convex polyhedron LPV systems with Markov jumping parameters
title_full_unstemmed Predictive control of convex polyhedron LPV systems with Markov jumping parameters
title_short Predictive control of convex polyhedron LPV systems with Markov jumping parameters
title_sort predictive control of convex polyhedron lpv systems with markov jumping parameters
url http://hdl.handle.net/20.500.11937/66246