Optimization of PID Controller to Stabilize Quadcopter Movements Using Meta-Heuristic Search Algorithms

Quadrotor UAVs are one of the most preferred types small unmanned aerial vehicles, due to their modest mechanical structure and propulsion precept. However, complex non-linear dynamic behavior Proportional Integral Derivative (PID) controller in these vehicles requires advanced stabilizing control movement. Additionally, locating appropriate gain for a model-based is relatively demands significant amount time, as it relies on external perturbations modeling plants. Therefore, developing method tuning quadcopter PID parameters may save effort better performance can be realized. Traditional methods, such Ziegler–Nichols (ZN), do not provide optimal might leave system with potential instability cause damage. One possible approach that alleviates tough task nonlinear design use meta-heuristics permit actions. This study presents using meta-heuristic algorithms, Genetic Algorithms (GAs), Crow Search Algorithm (CSA) Particle Swarm Optimization (PSO) stabilize movements. These were used position orientation based fitness function proposed reduce overshooting by predicting future paths. The obtained results confirmed efficacy felicitously reliably controlling flight GA, CSA PSO. Finally, simulation related movement PSO presented impressive results, compared GA CSA.