Girish Parmar

The application of Grey Wolf Optimizer (GWO) has been investigated for BH system. GWO is a novel meta-heuristic algorithm based on the hunting behavior of grey wolves. Numerous objective functions are available in the literature for optimization and tuning of PID controller. These have been minimized with the GWO to tune the proportional-integral-derivative (PID) controller, so that the BH system can be controlled. The simulation results illustrate the effectiveness of the proposed algorithm.

This paper deals with robustness and comparative analysis of GWO algorithm with different performance indices to control a system with perturbation. IAE, ISE, ITAE and ISTAE are different performance indices used in the present work for the optimization and tuning of the controller. These indices have been considered to be minimized by GWO algorithm to control the BH system. The robustness analysis has been carried out with ±5% perturbation in the location of the poles. The GWO tuned PID controller has also been applied on the perturbed systems. The comparative analysis has also been carried out for the system with perturbation in the poles.

Comparative analysis between Grey wolf optimization (GWO) and Sine Cosine algorithm (SCA) has been carried out for tuning the PID controller for speed control of DC motor. Due to simplicity and efficiency, the intelligent algorithms have gained the interest of researchers around the world for solving optimization problems. SCA is an optimization technique which creates multiple initial candidates' solutions moving towards the best solution using a mathematical model based on sine and cosine functions. The GWO is also a metaheuristic algorithm for solving complex problems. The performance of the PID controller tuned by both the algorithms has been compared in terms of responses, rise, settling times and overshoot. The GWO tuned PID controller outperforms the SCA tuned PID controller in terms of performance's parameters.

The Fractional Order-PID controller (FOPID) has been tuned by Grey Wolf Optimization (GWO) for speed control of DC motor. The integral of time multiplied absolute error (ITAE) has been taken as an objective function. The robustness analysis has also been shown with parameter's variations for the system under test. The simulation results show far better performance of FOPID tuned by GWO.