FOPID Corrector Tuning with Optimization Algorithms Applied on High Order Systems

In order to stabilize a particular class of higher order systems, this work contrasts algorithmic optimization with analytical/classical Ziegler-Nichols techniques for optimizing the fractional order FOPID controller. The technique is based on extending Zeigler-Nichol's methods to assimilate the open loop response of a higher order system to a first order system with delay. The parameters of the fractional FOPID correctors will then be ascertained. Then, optimization methods such as Genetic Algorithm (GA), Artificial Bee Colony (ABC), Particle Swarm Optimization (PSO), and Ant Colony Optimization (ACO) were used. In order to compare the simulated results, nonintrusive performance indices based on integral errors (ITAE) were developed. These indices were used to analyze and choose the best performance. A numerical simulation must ensure and validate the nearly zero overshoot and the stabilization time. In order to verify the robustness of the fractional regulator as optimized by the most suitable approach, a random variance will be applied to the parameters of the selected process.