Fuzzy PID Control Tuning Design Using Particle Swarm Optimization Algorithm for a Quadrotor

Abstract

This study focuses on tuning the parameters of proportional integral derivative controller (PID). These parameters are traditionally tuned through the Zeigler-Nichols method. However, fuzzy logic control is usually used to online adjust the PID controller parameters. Interestingly, to find the optimal fuzzy controller scaling factors, particle swarm optimization (PSO) may also be used. Nonetheless, in presence of multi-input multi-output (MIMO), nonlinear, and under-actuated systems, a multidimensional tune is necessary, which renders finding the optimal fuzzy-PID controller with PSO algorithm a difficult task. Then, this paper presents an adapted multidimensional PSO algorithm in order to improve the performances of a fuzzy-PID controller for stabilizing a quadrotor system when tracking its reference trajectory. Moreover, to show the effectiveness of this optimization strategy, it is shown that, using simulation tools, the fuzzy-PID controller that is tuned by the proposed multidimensional PSO algorithm could ensure better time domain specifications, in comparison with a classical PID controller.