FUZZY-GENETIC IDENTIFICATION AND CONTROL STUCTURES FOR NONLINEAR HELICOPTER MODEL
The paper exploits advantages of the genetic algorithm and fuzzy logic in identification and control of 2DOF nonlinear helicopter model. The genetic algorithm is proposed for identification of the helicopter system, which contains a helicopter body, main and tail motors and drivers. The quality of helicopter model achieved was validated through simulation and experimental modes. Then, this model is used to design of elevation and azimuth Mamdani type fuzzy controllers. The main objective of the paper is to obtain robust and stable controls for wide range of azimuth and elevation angles changing during the long time flight. The robustness and effectiveness of both fuzzy controllers were verified through both simulations and experiments. Also, a comparative analysis of proposed fuzzy and traditional PID controllers is performed.
helicopter model genetic algorithm fuzzy control identification process