Nature-inspired and hybrid optimization algorithms on interval Type-2 fuzzy controller for servo processes: a comparative performance study

In this paper, performance evaluations of six well-known nature-inspired algorithms have been reported containing genetic algorithm, cuckoo search, particle swarm optimization, differential evolution, bee colony, and combined particle swarm optimization and differential evolution (CPSODE) algorithms...

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Veröffentlicht in:SN applied sciences Jg. 2; H. 7; S. 1292
Hauptverfasser: De (Maity), Ritu Rani, Mudi, Rajani K., Dey, Chanchal
Format: Journal Article
Sprache:Englisch
Veröffentlicht: Cham Springer International Publishing 01.07.2020
Springer Nature B.V
Schlagworte:
3. Engineering (general)
Algorithms
Applied and Technical Physics
Chemistry/Food Science
Chromosomes
Closed loops
Comparative analysis
Controllers
Earth Sciences
Engineering
Environment
Evolutionary algorithms
Evolutionary computation
Fuzzy control
Fuzzy sets
Genetic algorithms
Materials Science
Mutation
Noise sensitivity
Objective function
Optimization algorithms
Particle swarm optimization
Performance evaluation
Proportional integral derivative
Random variables
Reliability analysis
Research Article
Scaling factors
Search algorithms
Servocontrol
Velocity
Genetic algorithm (GA)
Combined particle swarm optimization and differential evolution (CPSODE) algorithms
Interval Type-2 fuzzy controller
Particle swarm optimization (PSO)
Differential evolution (DE)
Bee colony (BC)
Servo tracking process
Cuckoo search (CS)
ISSN:2523-3963, 2523-3971
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Beschreibung
Zusammenfassung:In this paper, performance evaluations of six well-known nature-inspired algorithms have been reported containing genetic algorithm, cuckoo search, particle swarm optimization, differential evolution, bee colony, and combined particle swarm optimization and differential evolution (CPSODE) algorithms. Based on these optimization algorithms, input and output scaling factors of an interval Type-2 fuzzy PID controller (IT2-FLC) are chosen for closed-loop servo tracking. Optimal values of the scaling factors are chosen by minimization of the objective function which is defined based on the closed-loop controller performance criteria. A detailed comparative analysis is reported based on the simulation and experimental results. Performance analysis reveals that improved performance, reliability, robustness, and lesser noise sensitivity are reported by IT2-FLC with the optimal values obtained by the hybrid algorithm CPSODE.
Bibliographie:ObjectType-Article-1
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ObjectType-Feature-2
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ISSN:2523-3963
2523-3971
DOI:10.1007/s42452-020-3024-5