Advanced Metaheuristics-Based Approach for Fuzzy Control Systems Tuning - Complex System Modelling and Control Through Intelligent Soft Computations - page 616

but more especially the domain of process control design (Bouall gue et al.

2011 , 2012a , b ; David et al. 2013 ; Goswami and Chakraborty 2014 ; Madiouni et al.
2013 ; Toumi et al. 2014 ).
Various metaheuristics have been adopted by researchers. The Differential
Search Algorithm (DSA) (Civicioglu 2012 ), Gravitational Search Algorithm (GSA)
(Rashedi et al. 2009 ), Arti

è

cial Bee Colony (ABC) (Karaboga 2005 ) and Particle
Swarm Optimization (PSO) (Eberhart and Kennedy 1995 ; Kennedy and Eberhart
1995 ) algorithms are the most recent proposed techniques in the literature. They
will be adapted and improved for the considered fuzzy control design problem.
Without any regularity on the cost function to be optimized, the recourse to these
stochastic and global optimization techniques is justi ed by the empirical evidence

of their superiority in solving a variety of non-linear, non-convex and non-smooth
problems. In comparison with the conventional optimization algorithms, these
optimization techniques are a simple concept, easy to implement, and computa-
tionally ef

cient algorithms. Their stochastic behaviour allows overcoming the local
minima problem.
In this study, a new approach based on the use of advanced metaheuristics, such
as DSA, GSA, ABC and PSO is proposed for systematically tuning the scaling
factors of the particular PID-type FLC structure. The well known classical GAO
algorithm is used in order to compare the obtained optimization results (Goldberg
1989 ; MathWorks 2009 ). This work can be considered as a contribution on the
results given in Bouall

gue et al. ( 2012a , b ), Toumi et al. ( 2014 ). The synthesis and
tuning of the fuzzy controller are formulated as a constrained optimization problem
which is ef

è

ciently solved based on the proposed metaheuristics. In order to specify
more robustness and performance control objectives of the proposed metaheuris-
tics-tuned PID-type FLC, different optimization criteria such as ISE and MO are
considered and compared.
The remainder of this chapter is organized as follows. In Sect. 2 , the studied
PID-type FLC structure is presented and formulated as a constrained optimization
problem. An external static penalty technique is investigated to handle the problem
constraints. The advanced DSA, GSA, ABC and PSO metaheuristic algorithms, used
in solving the formulated problem, are described in Sect. 3 . Section 4 is dedicated
to apply the proposed fuzzy control approach on an electrical DC drive benchmark.
All obtained simulation results are compared with each other and analysed.
Experimental setup and results are presented within a real-time framework.

2 PID-Type FLC Tuning Problem Formulation

In this section, the PID-type fuzzy controller synthesis problem is formulated as a
constrained optimization problem which will be resolved through the suggested
metaheuristics algorithms.