Hybrid Particle Filter-Particle Swarm Optimization Algorithm and Application to Fuzzy Controlled Servo Systems

This article presents a hybrid metaheuristic optimization algorithm that combines particle filter (PF) and particle swarm optimization (PSO) algorithms. The new PF-PSO algorithm consists of two steps: the first generates randomly the particle population;and the second zooms the search domain. An app...

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Bibliographic Details
Published in:IEEE transactions on fuzzy systems Vol. 30; no. 10; pp. 4286 - 4297
Main Authors: Pozna, Claudiu, Precup, Radu-Emil, Horvath, Erno, Petriu, Emil M.
Format: Journal Article
Language:English
Published: New York IEEE 01.10.2022
The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subjects:
Algorithms
Cost function
Energy consumption
Fuzzy control
Fuzzy systems
Heuristic methods
Metaheuristics
optimization
particle filter (PF)
Particle swarm optimization
particle swarm optimization (PSO)
PF–PSO algorithm
Proportional integral
Search problems
Servocontrol
Sociology
Statistics
Tuning
ISSN:1063-6706, 1941-0034
Online Access:Get full text
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Description
Summary:This article presents a hybrid metaheuristic optimization algorithm that combines particle filter (PF) and particle swarm optimization (PSO) algorithms. The new PF-PSO algorithm consists of two steps: the first generates randomly the particle population;and the second zooms the search domain. An application of this algorithm to the optimal tuning of proportional-integral-fuzzy controllers for the position control of a family of integral-type servo systems is then presented as a second contribution. The reduction in PF-PSO algorithm's cost function allows for reduced energy consumption of the fuzzy control system. A comparison with other metaheuristic algorithms on canonical test functions and experimental results are presented at the end of this article.
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ISSN:1063-6706
1941-0034
DOI:10.1109/TFUZZ.2022.3146986