Design of an Intelligent Lateral Autopilot for Short Range Surface-to-Surface Aerodynamically Controlled Missile

Abstract

Technological growth had changed the conduction way of the warfare. This work is paying attention with developing the performance of a SSM (surface-to-surface missile) aerodynamically controlled system via both predictive and Neuro-Fuzzy controllers. The analysis and design demand somehow precise system model with different uncertainties via 6-DOF simulation. The executive differential equations of the missile motion are obtained from the model of missile’s aerodynamic that built by means of the Missile Datcom software. Hence getting the required aerodynamics stability derivatives by the resulted aerodynamics data, the required transfer functions are calculated based on the equations of motion for the missile. Then the yaw autopilot is designed using the calculated transfer functions and to recognize the command signal produced by the guidance laws. The form of guidance commands are in the lateral acceleration components. By using the whole system model, the computer simulators are made by using the Matlab-Simulink software, where predictive and hybrid AI (Artificial Intelligence) Neuro-Fuzzy Yaw autopilots are compared proving that the more stability and less processing time.