Adaptive Control of Nonlinear Systems Using Bacterial Foraging Algorithm

Abstract

 Abstract—In this paper bacterial foraging algorithm (BFA) have been implemented for indirect adaptive control of two nonlinear systems. The nonlinear systems considered in present analysis are liquid level control of surge tank and armature controlled DC motor speed control system. Simulation has been carried out in MATLAB. Using bacterial foraging algorithm plant nonlinearities component alpha and beta have been estimated and compared with actual plant nonlinearities for both the nonlinear systems. Liquid level estimated by BFA adaptive controller and actual liquid level has been compared in the liquid level nonlinear control system. Angular speed estimated by BFA adaptive controller and actual trajectory has been compared for DC motor speed control system. Fitness for the best member in the population of bacteria has been observed for both the nonlinear systems. In DC motor speed tracking obtained using indirect BFA adaptive control have been obtained and compared with reference one. Also liquid level set by indirect BFA adaptive controller have been obtained and compared with reference trajectory of level. Error plots show that error between desired and actual trajectory reduces after ten seconds of system operation in both nonlinear systems. Simulations studies have been also carried out through genetic algorithm (GA) for both nonlinear systems. A comparison of BFA results with GA shows that BFA based indirect adaptive controller are more effective in tracking the desired trajectory in both the nonlinear systems.