Computational Techniques for Model Predictive Control of Large-Scale Systems with Continuous-Valued and Discrete-Valued Inputs

We propose computational techniques for model predictive control of large-scale systems with both continuous-valued control inputs and discrete-valued control inputs, which are a class of hybrid systems. In the proposed method, we introduce the notion of virtual control inputs, which are obtained by...

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Main Authors: Koichi Kobayashi, Kunihiko Hiraishi
Format: Article
Language:English
Published: Hindawi Limited 2013-01-01
Series:Journal of Applied Mathematics
Online Access:http://dx.doi.org/10.1155/2013/615060
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spelling doaj-3f426729e08b48b7be84678817f7ab102020-11-25T01:08:30ZengHindawi LimitedJournal of Applied Mathematics1110-757X1687-00422013-01-01201310.1155/2013/615060615060Computational Techniques for Model Predictive Control of Large-Scale Systems with Continuous-Valued and Discrete-Valued InputsKoichi Kobayashi0Kunihiko Hiraishi1School of Information Science, Japan Advanced Institute of Science and Technology, Ishikawa 923-1292, JapanSchool of Information Science, Japan Advanced Institute of Science and Technology, Ishikawa 923-1292, JapanWe propose computational techniques for model predictive control of large-scale systems with both continuous-valued control inputs and discrete-valued control inputs, which are a class of hybrid systems. In the proposed method, we introduce the notion of virtual control inputs, which are obtained by relaxing discrete-valued control inputs to continuous variables. In online computation, first, we find continuous-valued control inputs and virtual control inputs minimizing a cost function. Next, using the obtained virtual control inputs, only discrete-valued control inputs at the current time are computed in each subsystem. In addition, we also discuss the effect of quantization errors. Finally, the effectiveness of the proposed method is shown by a numerical example. The proposed method enables us to reduce and decentralize the computation load.http://dx.doi.org/10.1155/2013/615060
collection DOAJ
language English
format Article
sources DOAJ
author Koichi Kobayashi
Kunihiko Hiraishi
spellingShingle Koichi Kobayashi
Kunihiko Hiraishi
Computational Techniques for Model Predictive Control of Large-Scale Systems with Continuous-Valued and Discrete-Valued Inputs
Journal of Applied Mathematics
author_facet Koichi Kobayashi
Kunihiko Hiraishi
author_sort Koichi Kobayashi
title Computational Techniques for Model Predictive Control of Large-Scale Systems with Continuous-Valued and Discrete-Valued Inputs
title_short Computational Techniques for Model Predictive Control of Large-Scale Systems with Continuous-Valued and Discrete-Valued Inputs
title_full Computational Techniques for Model Predictive Control of Large-Scale Systems with Continuous-Valued and Discrete-Valued Inputs
title_fullStr Computational Techniques for Model Predictive Control of Large-Scale Systems with Continuous-Valued and Discrete-Valued Inputs
title_full_unstemmed Computational Techniques for Model Predictive Control of Large-Scale Systems with Continuous-Valued and Discrete-Valued Inputs
title_sort computational techniques for model predictive control of large-scale systems with continuous-valued and discrete-valued inputs
publisher Hindawi Limited
series Journal of Applied Mathematics
issn 1110-757X
1687-0042
publishDate 2013-01-01
description We propose computational techniques for model predictive control of large-scale systems with both continuous-valued control inputs and discrete-valued control inputs, which are a class of hybrid systems. In the proposed method, we introduce the notion of virtual control inputs, which are obtained by relaxing discrete-valued control inputs to continuous variables. In online computation, first, we find continuous-valued control inputs and virtual control inputs minimizing a cost function. Next, using the obtained virtual control inputs, only discrete-valued control inputs at the current time are computed in each subsystem. In addition, we also discuss the effect of quantization errors. Finally, the effectiveness of the proposed method is shown by a numerical example. The proposed method enables us to reduce and decentralize the computation load.
url http://dx.doi.org/10.1155/2013/615060
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AT kunihikohiraishi computationaltechniquesformodelpredictivecontroloflargescalesystemswithcontinuousvaluedanddiscretevaluedinputs
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