Intelligent Auto pilot Design for a Nonlinear Model of an Autonomous Helicopter by Adaptive Emotional Approach

There is a growing interest in the modeling and control of model helicopters using nonlinear dynamic models and nonlinear control. Application of a new intelligent control approach called Brain Emotional Learning Based Intelligent Controller (BELBIC) to design autopilot for an autonomous helicopter is addressed in this paper. This controller is applied to a nonlinear model of a helicopter. This methodology has been previously proved to present robust characteristics against disturbances and uncertainties existing in the system. The simulation results of this controller has compared with a PID controller. The policies for PID and BELBIC controller are the same. The controller design goal is that the helicopter tracks a special maneuver to reach the commanded height and heading. The performance of the controllers is also evaluated for robustness against perturbations with inserting a high frequency disturbance. Simulation results show a desirable performance in both tracking and improved control signal by using BELBIC controller.