Abstract
In this paper, we tackle the problem of PID Control tuning for a quadrotor. This task is vital given the several applications a UAV quadrotor can perform. This paper focuses on the optimal PID controller tuning in ø axes. We propose using a Multi-objective Particle Swarm Optimization (PSO) algorithm for PID performance improvement. The proposed system is evaluated in a Parrot Mambo FPV UAV Quadrotor virtual model using MATLAB & Simulink environment. We compare four different cost functions for the multi-objective optimization approach. Those cost functions focus on improving the UAV performance based on the settling time, overshoot, steady-state error, and control effort. The evaluation system shows the best performance in combining the different factors through the Multi-objective PSO algorithm.
Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
