A Comparison of RECCO and FCPFC Controller on Nonlinear Chemical Reactor

Goran Andonovski; Edwin Lughofer; Igor Skrjanc

A Comparison of RECCO and FCPFC Controller on Nonlinear Chemical Reactor

Goran Andonovski
, Edwin Lughofer
, Igor Skrjanc

Institute for Mathematical Methods in Medicine and Data Based Modeling

Research output: Chapter in Book/Report/Conference proceeding › Conference proceedings › peer-review

Abstract

In this paper we present a performance comparison between a new fuzzy (cloud-based) predictive functional control (FCPFC) and the Robust Evolving Cloud-based controller (RECCo). Both methods use the same type of fuzzy cloud-based system (same antecedent part) where the clouds are used for partitioning the data space and dealing with non-linearity of the process. In case of FCPFC the cloud-based fuzzy model is used to identify the process model and control signal is analytically calculated to minimize some criterion. While in case of RECCo algorithm the clouds are used to identify the operating region and the control signal is adapted in online manner. The controllers were tested on a second order nonlinear, locally unstable, chemical reactor CSTR (Continuous Stirred Tank Reactor). The performance and control effort of the methods were compared according to several criteria.

Original language	English
Title of host publication	Proc. of The 36th IASTED International Conference on Modelling, Identification and Control
Place of Publication	Innsbruck, Austria
Publisher	ACM
Number of pages	8
Publication status	Published - Feb 2017

Publication series

Name	IASTED Proceedings

Fields of science

101 Mathematics
101013 Mathematical logic
101024 Probability theory
102001 Artificial intelligence
102003 Image processing
102019 Machine learning
603109 Logic
202027 Mechatronics

JKU Focus areas

Computation in Informatics and Mathematics
Mechatronics and Information Processing
Nano-, Bio- and Polymer-Systems: From Structure to Function

Cite this

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title = "A Comparison of RECCO and FCPFC Controller on Nonlinear Chemical Reactor",

abstract = "In this paper we present a performance comparison between a new fuzzy (cloud-based) predictive functional control (FCPFC) and the Robust Evolving Cloud-based controller (RECCo). Both methods use the same type of fuzzy cloud-based system (same antecedent part) where the clouds are used for partitioning the data space and dealing with non-linearity of the process. In case of FCPFC the cloud-based fuzzy model is used to identify the process model and control signal is analytically calculated to minimize some criterion. While in case of RECCo algorithm the clouds are used to identify the operating region and the control signal is adapted in online manner. The controllers were tested on a second order nonlinear, locally unstable, chemical reactor CSTR (Continuous Stirred Tank Reactor). The performance and control effort of the methods were compared according to several criteria.",

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A Comparison of RECCO and FCPFC Controller on Nonlinear Chemical Reactor. / Andonovski, Goran; Lughofer, Edwin; Skrjanc, Igor.
Proc. of The 36th IASTED International Conference on Modelling, Identification and Control. Innsbruck, Austria: ACM, 2017. (IASTED Proceedings).

Research output: Chapter in Book/Report/Conference proceeding › Conference proceedings › peer-review

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AU - Skrjanc, Igor

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N2 - In this paper we present a performance comparison between a new fuzzy (cloud-based) predictive functional control (FCPFC) and the Robust Evolving Cloud-based controller (RECCo). Both methods use the same type of fuzzy cloud-based system (same antecedent part) where the clouds are used for partitioning the data space and dealing with non-linearity of the process. In case of FCPFC the cloud-based fuzzy model is used to identify the process model and control signal is analytically calculated to minimize some criterion. While in case of RECCo algorithm the clouds are used to identify the operating region and the control signal is adapted in online manner. The controllers were tested on a second order nonlinear, locally unstable, chemical reactor CSTR (Continuous Stirred Tank Reactor). The performance and control effort of the methods were compared according to several criteria.

AB - In this paper we present a performance comparison between a new fuzzy (cloud-based) predictive functional control (FCPFC) and the Robust Evolving Cloud-based controller (RECCo). Both methods use the same type of fuzzy cloud-based system (same antecedent part) where the clouds are used for partitioning the data space and dealing with non-linearity of the process. In case of FCPFC the cloud-based fuzzy model is used to identify the process model and control signal is analytically calculated to minimize some criterion. While in case of RECCo algorithm the clouds are used to identify the operating region and the control signal is adapted in online manner. The controllers were tested on a second order nonlinear, locally unstable, chemical reactor CSTR (Continuous Stirred Tank Reactor). The performance and control effort of the methods were compared according to several criteria.

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BT - Proc. of The 36th IASTED International Conference on Modelling, Identification and Control

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