Fuzzy-model-based hybrid predictive control

Alfredo Núñez; Doris Sáez; Simon Oblak; Igor Škrjanc

doi:10.1016/j.isatra.2008.10.007

Fuzzy-model-based hybrid predictive control

Alfredo Núñez, Doris Sáez^*, Simon Oblak, Igor Škrjanc

^*Corresponding author for this work

Research output: Contribution to journal › Article › Scientific › peer-review

30 Citations (Scopus)

Abstract

In this paper we present a method of hybrid predictive control (HPC) based on a fuzzy model. The identification methodology for a nonlinear system with discrete state-space variables based on combining fuzzy clustering and principal component analysis is proposed. The fuzzy model is used for HPC design, where the optimization problem is solved by the use of genetic algorithms (GAs). An illustrative experiment on a hybrid tank system is conducted to demonstrate the benefits of the proposed approach.

Original language	English
Pages (from-to)	24-31
Number of pages	8
Journal	ISA Transactions
Volume	48
Issue number	1
DOIs	https://doi.org/10.1016/j.isatra.2008.10.007
Publication status	Published - 1 Jan 2009
Externally published	Yes

Keywords

Fuzzy model
Genetic algorithm
Hybrid systems
Predictive control

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10.1016/j.isatra.2008.10.007

Cite this

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abstract = "In this paper we present a method of hybrid predictive control (HPC) based on a fuzzy model. The identification methodology for a nonlinear system with discrete state-space variables based on combining fuzzy clustering and principal component analysis is proposed. The fuzzy model is used for HPC design, where the optimization problem is solved by the use of genetic algorithms (GAs). An illustrative experiment on a hybrid tank system is conducted to demonstrate the benefits of the proposed approach.",

keywords = "Fuzzy model, Genetic algorithm, Hybrid systems, Predictive control",

author = "Alfredo N{\'u}{\~n}ez and Doris S{\'a}ez and Simon Oblak and Igor {\v S}krjanc",

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AU - Oblak, Simon

AU - Škrjanc, Igor

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N2 - In this paper we present a method of hybrid predictive control (HPC) based on a fuzzy model. The identification methodology for a nonlinear system with discrete state-space variables based on combining fuzzy clustering and principal component analysis is proposed. The fuzzy model is used for HPC design, where the optimization problem is solved by the use of genetic algorithms (GAs). An illustrative experiment on a hybrid tank system is conducted to demonstrate the benefits of the proposed approach.

AB - In this paper we present a method of hybrid predictive control (HPC) based on a fuzzy model. The identification methodology for a nonlinear system with discrete state-space variables based on combining fuzzy clustering and principal component analysis is proposed. The fuzzy model is used for HPC design, where the optimization problem is solved by the use of genetic algorithms (GAs). An illustrative experiment on a hybrid tank system is conducted to demonstrate the benefits of the proposed approach.

KW - Fuzzy model

KW - Genetic algorithm

KW - Hybrid systems

KW - Predictive control

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JO - ISA Transactions

JF - ISA Transactions

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Fuzzy-model-based hybrid predictive control

Abstract

Keywords

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