A Modified PSO Algorithm for IIR Digital Filter Modeling

Modeling for an unknown plant is a very important and primary task in the control system engineering. By using this established model, an adequate controller can be further designed to meet certain control specifications. This paper will propose a new modeling method which is based on the infinite i...

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Published inJournal of circuits, systems, and computers Vol. 27; no. 5; p. 1850073
Main Author Chang, Wei-Der
Format Journal Article
LanguageEnglish
Published Singapore World Scientific Publishing Company 01.05.2018
World Scientific Publishing Co. Pte., Ltd
Subjects
Algorithms
Computer simulation
Control systems design
Digital filters
Digital systems
IIR filters
Impulse response
Model reduction
Modelling
Particle swarm optimization
multiple subpopulations
IIR digital filter
PSO algorithm
Online AccessGet full text
ISSN0218-1266
1793-6454
DOI10.1142/S0218126618500731

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Abstract Modeling for an unknown plant is a very important and primary task in the control system engineering. By using this established model, an adequate controller can be further designed to meet certain control specifications. This paper will propose a new modeling method which is based on the infinite impulse response (IIR) digital filter structure. A modified particle swarm optimization (PSO) with multiple subpopulations is utilized to solve for the IIR filter coefficients to model an unknown digital system. The developed PSO algorithm is able to overcome the multimodal error surface problem that often occurs in the system modeling of IIR digital filter. Finally, three different kinds of digital systems are examined to demonstrate the feasibility of the proposed method, including the same system order and reduced order structures. It is concluded from several simulation results that the proposed method has an excellent performance on solving the IIR digital modeling problem.
AbstractList Modeling for an unknown plant is a very important and primary task in the control system engineering. By using this established model, an adequate controller can be further designed to meet certain control specifications. This paper will propose a new modeling method which is based on the infinite impulse response (IIR) digital filter structure. A modified particle swarm optimization (PSO) with multiple subpopulations is utilized to solve for the IIR filter coefficients to model an unknown digital system. The developed PSO algorithm is able to overcome the multimodal error surface problem that often occurs in the system modeling of IIR digital filter. Finally, three different kinds of digital systems are examined to demonstrate the feasibility of the proposed method, including the same system order and reduced order structures. It is concluded from several simulation results that the proposed method has an excellent performance on solving the IIR digital modeling problem.
Author Chang, Wei-Der
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crossref_primary_10_1155_2018_6468517
crossref_primary_10_1186_s43067_023_00102_4
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SubjectTerms Algorithms
Computer simulation
Control systems design
Digital filters
Digital systems
IIR filters
Impulse response
Model reduction
Modelling
Particle swarm optimization
Title A Modified PSO Algorithm for IIR Digital Filter Modeling
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