Discovering and Optimizing New NonLinear Flight Control Laws Through Genetic Programming

Synthesis of radically new feedback guidance and control laws for high performance aircraft using genetic programming is proposed. Starting from an initial population of computer programs implementing familiar flight control laws, the proposed methodology employs the processes of natural selection and genetics to synthesize new populations of computer programs exhibiting improved degrees of fitness. Phase I research will involve the development of a flight control system and an intercept guidance system. Fitness criterion for flight control includes factors such as stability, robustness, tracking performance and flying qualities. Fitness criterion for guidance law consists of time-to-intercept, intantaneous acceleration magnitude and line-of-sight rate. The proposed method will produce directly implementable flight control computer code in ANSI C language.