Adaptive control of DC motor using bacterial foraging algorithm

This paper introduces a bacterial foraging algorithm (BFA) based high performance speed control system for a DC motor. The rotor speed of the DC motor is being made to follow an arbitrary selected trajectory. The unknown nonlinear dynamics of the motor and the load are captured by BFA. The trained BFA identifier is used with a desired reference model to achieve trajectory control of DC motor. In this paper bacterial foraging algorithm (BFA) has been implemented for identification and control of DC motor. Simulation study on proposed system has been carried out in MATLAB. System nonlinearities alpha and beta have been estimated using BFA and compared with actual plant nonlinearities of dynamical system. In tracking of motor speed using BFA based controller the performance of the motor have been observed and compared with reference one. Performance study of DC motor has been carried out through genetic algorithm (GA) also. A comparison of performance analysis using BFA controller and that of GA for trajectory tracking shows that BFA based adaptive controller works effectively for tracking the desired trajectory in DC motor with less computational time.