Ant colony optimization of type-2 fuzzy helicopter controller

Many works have been done for controlling nonlinear systems using bio-inspired methods. In this paper, we propose an optimal intelligent controller for an Unmanned Aerial Vehicle (UAV). The controller consists on a type-2 fuzzy system with defuzzifier step was determined through Ant Colony Optimization algorithm (ACO). It is known that, ACO and Particle Swarm Optimization (PSO) algorithm are the most powerful bio-inspired optimization methods. Then, performances of ACO and PSO were compared. All optimized controllers were applied to Birotor helicopter system. Simulations results were given to show superiority of ACO compared with PSO and the classical case (type-2 fuzzy controller without optimization).