A genetic algorithm is used to optimize the membership functions and rule bases of a multi-stage fuzzy PID controller with a fuzzy switch. The multistage controller uses the fuzzy switch to blend a proportional-plus-derivative fuzzy logic controller with an integral fuzzy logic input. The multi-stage structure operates on fuzzy values by passing the consequence of a prior stage onto the next stage as fact. The genetic algorithm is used to optimize the large number of variables across a range of inputs and operating states. A sample run of the genetic algorithm produces a controller with better rise time, overshoot and settling time than both a classical PID controller and a multi-stage fuzzy PID controller tuned by an intuitive method. The genetic algorithm designed controller is compared to the intuitive controller.