The Use of an Optimal Fuzzy Controller Algorithm for a Low-cost Microcontroller

Abstract

Fuzzy gain-scheduled PID (FuGSPID) controllers have attracted significant interest in contemporary research. This paper provides mathematical description help to reduce the code program for a Fuzzy gain-scheduled controller FuGSPID that is subsequently used to stabilize the altitude of a home-constructed Quadcopter. The subject particle swarm optimization approach was employed to optimize the fuzzy output sets of the controller. MATLAB was used to generate the dynamic model, the FuGSPID, and the optimization. A simulation exercise revealed that the new parameters employed in the FuGSPID that were generated as a result of the particle swarm optimization produced fewer trajectory tracking errors. Fuzzy systems are required to process large volumes of tasks and processes. This subsequently impedes the performance of the microcontroller. In light of this, this paper outlines a mathematical description that can potentially reduce the algorithm code employed in the FuGSPID controller and, thereby, making it more intuitive and reducing the processing speed of the microcontroller and reducing the sampling time of the controller and the whole flight controller. The findings of this study revealed that the mathematical description it be useful to reduce instruction of fuzzy controller program to implement it in low cost microcontroller and tested effectively for a quadcopter altitude stabilization.