Metaheuristic based optimization for tuning of PID controllers for DC motor parameters.

Dc motors represent linear systems up to point of saturation. In this paper, optimized tuning of DC motors has been discussed with the help of different meta-heuristic algorithms. The model of the DC motor is basically a third-order system. Dc motors, that are used in different industrial applications including conveyors, turntables, and other places where adjustable speed and constant or low-speed torques are required, owing to their simple configuration. They also find its application in dynamic braking and reversing applications as well. Here, in this paper Genetic Algorithm, Differential Evolution, Teaching Learning Based Optimization, Particle Swarm Optimization with different performance indices (Mean Square Error and Integral time absolute error) is compared with the standard Ziegler & Nichols method. Comparison of results using standard step parameters i.e., maximum overshoot, steady-state, rise time and peak time, etc. is being discussed. [ABSTRACT FROM AUTHOR]