The robust search characteristics of evolutionary algorithms have been used successfully in the evolution of rule based systems for a variety of problems, although many difficulties still remain. In this talk we examine the use of evolutionary algorithms in evolving rule based systems for dynamic control problems. The proposed method evolves both controller structure and parameters simultaneously. The rule based representation allows the proposed control method to be comprehensable by a human observer. As a case study, we apply the method to the well known cart pole problem, and find that we can balance the cart from a range of initial values for an extended period of time.