New Deterministic Optimization Algorithm for Fuzzy Control Tuning Design of a Quadrotor

Abstract

Using an optimization algorithm to find the optimal controller parameters is still a big challenge. This paper proposes a new algorithm to tune the scaling gains of a fuzzy logic controller. Based on a deterministic choice of the population, the proposed algorithm allows determining the best parameters of a fuzzy logic controller that is used to stabilize the position of a quadrotor system when tracking specified trajectories. In addition, using simulation tools, it is shown that a fuzzy controller which is optimized by the proposed algorithm could give similar performances to the case of particle swarm optimization design. Thus, from these simulation results, it is also shown that this tuning approach actually gives fast and complete way to optimize any controller, which makes the new deterministic algorithm a good addition to solving controller tuning problems.