Mixed robust controller with optimized weighted selection for a DC servo motor

This paper presents an intelligent scheme to improve the performance of the H infinity controller by selecting a suitable weighting function that ensures a robust loop shaping control. In general, the weighting function is selected by trial and error. Recently the optimization algorithms had been developed and used widely to solve complex problems and in this paper, one of the effective optimization methods (Particle Swarm Optimization) is applied to select optimum parameters of the controller that achieves robustness response against system uncertainty with good time performance. However, a good weighting function designed by selecting a suitable objective function based on combining H infinity with H2 control schemes. Simulation results confirm that the proposed control scheme satisfies the robust stability, robust performance and provide a good tracking performance in spite of systematic uncertainties and external disturbance. Moreover, the performance of the proposed controller is compared with other control methods. The simulation results illustrated the effectiveness of the proposed control method.