Real-Time Trajectory Tracking Control for UAVs via Online Genetic Algorithm-Based PID Optimization

Shaimaa Hadi  Mohammad

Authors

Shaimaa Hadi Mohammad Ministry of Education, University of Sumer, College of Engineering, Department of Mechanical Engineering

Keywords:

Unmanned Aerial Vehicle (UAV), trajectory tracking control, adaptive PID, online genetic algorithm (OGA), real-time control, nonlinear UAV dynamics, gain optimization

Abstract

This paper presents a real-time trajectory tracking control strategy for unmanned aerial vehicles (UAVs) based on Online Genetic Algorithm (OGA) for proportional integral derivative (PID) controller optimization. The designed OGA-PID system adaptively changes controller gains during flight, providing robust adaptation against disturbances, noise, and changing operating conditions. A nonlinear UAV system was simulated under several reference trajectories, such as circular, figure-eight and helical trajectories, with performance measured through Monte Carlo experiments. Comparative results versus a baseline fixed-gain PID controller show that the OGA-PID method greatly minimizes tracking error of the X, Y and Z axes while providing smooth control input. Quantitative indices of performance, ISE, IAE and ITAE, also affirm systematic improvements of all trajectories. In addition, adaptive gain evolution during OGA updating reveals the capability of the algorithm to adjust control parameter settings at real time. the developed approach improves UAV trajectory tracking performance and robustness and presents a viable system framework for intelligent adaptive flight control.

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