Advanced Metaheuristics-Based Approach for Fuzzy Control Systems Tuning - Complex System Modelling and Control Through Intelligent Soft Computations - page 630

Table 3 Optimization results
from 20 trials of problem
(1.1): ISE criterion

Algorithm Best Mean Worst ST deviation

DSA 0.1621 0.1691 0.1760 0.0045

GSA 0.1556 0.1710 0.1800 0.0193

ABC 0.1928 0.2274 0.2322 0.0134

PSO 0.1600 0.1715 0.1802 0.0140

GAO 0.1643 0.1722 0.1799 0.0086

Table 4 Optimization results
from 20 trials of problem
(1.1): MO criterion

Algorithm Best Mean Worst ST deviation

DSA 0.0365 0.0722 0.1307 0.0277

GSA 0.0307 0.0624 0.0096 0.0315

ABC 0.1305 0.1550 0.1972 0.0412

PSO 0.0422 0.0936 0.1420 0.0511

GAO 0.0411 0.0913 0.1300 0.0373

p 1 =0.3; p 2 =0.3
p 1 =0.1; p 2 =0.1
p 1 =0.1; p 2 =0.2
p 1 =1.5; p 2 =2.0

0.3

0.25

0.2

0.15

0 20 40 60 80 100

Iteration

Fig. 5 Robustness convergence under control parameters variation of the DSA-based approach:
ISE criterion case

In this case study, we tested the proposed algorithms with different values of the
population size in the range of [20, 50]. Globally, all the results found are close to
each other. The best values of this control parameter are usually obtained while
using a population size equal to 30.