Novel Adaptive Gravitational Search Algorithm for Fuzzy Controlled Servo Systems

This paper presents a novel adaptive Gravitational Search Algorithm (GSA) for the optimal tuning of fuzzy controlled servo systems characterized by second-order models with an integral component and variable parameters. The objective functions consist of the output sensitivity functions of the sensi...

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Bibliographic Details
Published in:IEEE transactions on industrial informatics 2012-11, Vol.8 (4), p.791-800
Main Authors: Precup, Radu-Emil, David, R., Petriu, E. M., Preitl, S., Radac, M.
Format: Article
Language:English
Subjects:
Adaptation models
Adaptive algorithms
Adaptive control systems
Adaptive gravitational search algorithm
experimental results
Fuzzy
Fuzzy control
Fuzzy logic
Fuzzy set theory
Mathematical models
Optimization
parametric sensitivity
Process control
servo systems
Servomotors
Servosystems
small time constant
Tuning
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Summary:This paper presents a novel adaptive Gravitational Search Algorithm (GSA) for the optimal tuning of fuzzy controlled servo systems characterized by second-order models with an integral component and variable parameters. The objective functions consist of the output sensitivity functions of the sensitivity models defined with respect to the parametric variations of the processes. The proposed adaptive GSA solves the optimization problems resulting in a new generation of Takagi-Sugeno proportional-integral fuzzy controllers (T-S PI-FCs) with a reduced time constant sensitivity. A design method for T-S PI-FCs is then proposed and experimentally validated in the representative case study of the optimal tuning of T-S PI-FCs for the position control system of a servo system.
ISSN:1551-3203
1941-0050
DOI:10.1109/TII.2012.2205393