The use of genetic algorithms and genetic programming in control engineering has started to expand in the last few years. This is mainly for two reasons: the physical cost of implementing a known control algorithm and the difficulty to find such an algorithm for complex plants . Broadly, evolutionary algorithms for control can be classified as either “pure” evolutionary or hybrid architectures. This chapter reviews some of the most successful applications of genetic algorithms and genetic programming in control engineering and outlines some general principles behind such applications. Demonstration of the power of these techniques is given, by describing how a hybrid genetic controller can be applied to the control of complex (even chaotic) dynamic systems. In particular, the detumbling and attitude control problems of a satellite are considered.