Fuzzy logic controller for UAV with gains optimized via genetic algorithm

A gains optimizer of a fuzzy controller system for an Unmanned Aerial Vehicle (UAV) based on a metaheuristic algorithm is developed in the present investigation. The contribution of the work is the adjustment by the Genetic Algorithm (GA) to tune the gains at the input of a fuzzy controller. First, a typical fuzzy controller was modeled, designed, and implemented in a mathematical model obtained by Newton-Euler methodology. Subsequently, the control gains were optimized using a metaheuristic algorithm. The control objective is that the UAV consumes the least amount of energy. With this basis, the Genetic Algorithm finds the necessary gains to meet the design parameters. The tests were performed using the Matlab-Simulink environment. The results indicate an improvement, reducing the error in tracking trajectories from 30% in some tasks and following trajectories that could not be completed without a tuned controller in other tasks.