International Journal of Research & Review (www.ijrrjournal.com) 101 Vol.5; Issue: 10; October 2018 International Journal of Research and Review www.ijrrjournal.com E-ISSN: 2349-9788; P-ISSN: 2454-2237 Research Paper Optimization of PID Controller Using Crow Search Algorithm and Bat Algorithm A. A. A. Wahab, S. S. N. Alhady, N. H. B. Sofik, W. A. F. W. Othman School of Electric and Electronic Engineering, Universiti Sains Malaysia (USM) Transkrian, Nibong Tebal, Pulau Pinang, Malaysia Corresponding Author: S. S. N. Alhady ABSTRACT Engineering field usually requires the best design for an optimum performance, thus optimization plays an important part in this field. Among optimization algorithms, crow search algorithm (CSA) and bat algorithm (BA) were chosen for this study. In this study, the effectiveness of CSA and BA were compared by analyzing the minimization of objective function and the step responses of the closed loop systems with proportional-integral-differential (PID) controller. The four criteria of objective functions are comprised as overshoot, settling time, rise time and steady state error. These are compared with acceptable solutions and the best one is selected with respect to optimized design. The parameters of PID controller i.e. K p , K i and K d must be properly selected as the selection affects the transient response of a system. The best combination of parameters will reduce problems such as nonlinearities encountered by industrial plants. Then, comparisons and investigations were made based on the average and standard deviation of cost returned by the cost function. It can be seen that the ability to subdivide automatically in BA search was a short one in finding the optimal solutions. The results show improvement 1.06% in overshoot percentage after modification. The objective function value is increased for BA 1.443e-04 and the CSA is 7.5113e-07 considering the performance parameter needs to be optimized to minimize the error signal. Even though BA had a lower convergence rate compared to CSA but it managed to find the optimal solutions. Keywords: PID controller; Crow Search algorithm; Bat Algorithm; Error criteria INTRODUCTION The main objective of this paper is to identify a suitable optimization algorithm to tune and to develop PID controller for brushed DC motor application. There is a lot of intelligent tuning methods such as genetic algorithm (GA), particle swarm optimization (PSO), bacterial foraging (BF) and many more (Ibrahim et al., 2014). There are a significant number of new algorithms created in recent years to solve complex problems. Proportional-Integral-Derivative (PID) controller is widely used for speed and position control of DC motor (Jaiswal and Phadnis, 2013). DC motor has been a part of the industry despite the fact that its maintenance cost is higher than the induction motor. In the optimization algorithm, the design objective could be simply to minimize the cost function or to maximize the efficiency of production. An optimization algorithm is a procedure which is executed iteratively by comparing various solutions till an optimum or a satisfactory solution is found (Wang et al., 2017). Optimization algorithm is a procedure which is executed iteratively by comparing various solutions till an optimum