Optimal control using fuzzy logic and evolutionary algorithms

In this paper we show how to use evolutionary algorithms to find a nonlinear, feedback, fuzzy controller to solve optimal control problems. In particular, we study the continuous stirred tank reactor optimal control problem and a problem in which the state equations contain a non-differentiable component of a rectangular pulse over a subinterval of the time range Results are compared with the iterative dynamic programming technique.