SWARM INTELLIGENCE, VOL 3: APPLICATIONS, vol.119, pp.245-281, 2018 (SCI-Expanded)
In this chapter, particle swarm optimization, ant colony optimization, artificial bee colony optimization and cuckoo search optimization are examined in detail. Differences, advantages and disadvantages of these algorithms are emphasized clearly. Performances of the swarm algorithms in terms of computing time, computing complexity and accuracy and convergence behavior are compared each other. As application area, fractional control systems from new attractive topics of control are chosen. In this chapter, the fractional order proportional integral derivative controllers are tuned with the swarmalgorithms using objective functions such as integral of absolute error, integral of the squared error, the integral of time multiplied by the absolute error and integral of time multiplied by the squared error. The simulation results can be used to determine which swarm algorithms yield better search performance in the multiobjective and high-dimensional nonlinear constrained optimization problems such as the fractional order control systems.