Learning of Intelligent Controllers for Autonomous Unmanned Combat Aerial Vehicles by Genetic Cascading Fuzzy Methods
Looking forward to an autonomous Unmanned Combat Aerial Vehicle (UCAV) for future applications, it becomes apparent that on-board intelligent controllers will be necessary for these advanced systems. LETHA (Learning Enhanced Tactical Handling Algorithm) was created to develop intelligent managers for these advanced unmanned craft through the novel means of a genetic cascading fuzzy system. In this approach, a genetic algorithm creates rule bases and optimizes membership functions for multiple fuzzy logic systems, whose inputs and outputs feed into one another alongside crisp data. A simulation space referred to as HADES (Hoplological Autonomous Defend and Engage Simulation) was created in which LETHA can train the UCAVs intelligent controllers.