Advanced Metaheuristics-Based Approach for Fuzzy Control Systems Tuning - Complex System Modelling and Control Through Intelligent Soft Computations - page 614

Advanced Metaheuristics-Based Approach
for Fuzzy Control Systems Tuning

Sou ene Bouall gue, Fatma Toumi, Joseph Hagg ge

è è

and Patrick Siarry

Abstract In this study, a new advanced metaheuristics-based optimization
approach is proposed and successfully applied to design and tuning of a PID-type
Fuzzy Logic Controller (FLC). The scaling factors tuning problem of the FLC
structure is formulated and systematically resolved, using various constrained
metaheuristics such as the Differential Search Algorithm (DSA), Gravitational
Search Algorithm (GSA), Arti cial Bee Colony (ABC) and Particle Swarm Opti-

mization (PSO). In order to specify more time-domain performance control objec-
tives of the proposed metaheuristics-tuned PID-type FLC, different optimization
criteria such as Integral of Square Error (ISE) and Maximum Overshoot (MO) are
considered and compared The classical Genetic Algorithm Optimization (GAO)
method is also used as a reference tool to measure the statistical performances of the
proposed methods. All these algorithms are implemented and analyzed in order to
show the superiority and the effectiveness of the proposed fuzzy control tuning
approach. Simulation and real-time experimental results, for an electrical DC drive
benchmark, show the advantages of the proposed metaheuristics-tuned PID-type
fuzzy control structure in terms of performance and robustness.