Fuzzy Neural Control Design Software for Multiple Effector Control Systems

In this Phase I project, a fuzzy neural control design software tool will be developed with the Genetic Algorithms (GAs) based adaptive fuzzy neural control method to enhance the performance and autonomous control ability of multiple effector control systems. First, a fuzzy logic control algorithm will be developed. Second, the GAs will be used to form a self-learning and self-tuning mechanism to tune the membership parameters and modify the rules. A fuzzy neural algorithm will also be developed. With the GAs based adaptive fuzzy neural control system the performance of the multiple effector control systems will be improved significantly in the presence of disturbances and uncertainties. Finally, a software toolkit will be developed and commercialized for the design, analysis and demonstration of genetic algorithms based adaptive fuzzy logic control systems. The software will be developed using the software engineering, object-oriented and Windows programming techniques. It provides a graphical user-friendly interface and design and analysis functions for autonomous intelligent control. In order to demonstrate the effectiveness of the toolkit, it will be used to design an autopilot for a tactical ballistic missile. Then, nonlinear 6 DOF simulation will be conducted to evaluate the design.