Development of a nature inspired algorithm based controller for DC servo motor

Proportional-Integral-Derivative (PID) controller is incorporated in Direct-Current (DC) servo motor control application due to its efficiency and ease of implementation. Nevertheless, the existing PID tuning methods are time consuming, and yet expertise and experience are required. Therefore, new approaches to tune PID controller is very important with the aim of obtaining better performances. The objective of this research is to investigate nature inspired algorithms used in PID controller tuning optimization. The simulation results show that both meta-heuristic algorithms Simulated Annealing (SA) and Differential Evolution (DE) based PID controller produce better performance compared with Ziegler Nichols (ZN) PID controller.