In this paper, a methodology for designing a controller based on inverse dynamics for speed control of DC motors is presented. The proposed controller has robustness in disturbance and it consists of a prefilter, the inverse dynamic model of a system and a fuzzy logic controller. The prefilter prevents high frequency effects from the inverse dynamic model. The model of the system is characterized by a nonlinear equation with coulomb friction and viscous friction. The fuzzy logic controller(FLC) is characterized by fuzzy "If-then" rules which represent locally linear control output whose consequence part is defined as linear PI controllers. And it regulates the error between the set-point and the system output which may be caused by disturbances and it simultaneously traces the change of the reference input.
A real coded genetic algorithm estimates the parameters of both the model and the linear PI controller. And it is characterized by three basic genetic operators that can deal with real coding chromosomes.
An experimental work on a DC motor system is carried out to illustrate the performance of the proposed controller.