Intelligent PD Control of a Coaxial Birotor UAV for Precise Trajectory Tracking Using Metaheuristic Algorithms

Mohamed AZEGMOUT, Mostafa MJAHED, Abdeljalil EL KARI, Hassan AYAD

Abstract

This paper presents the design and optimization of a Proportional-Derivative (PD) control scheme for tracking the trajectory of a coaxial birotor unmanned aerial vehicle (UAV). The mathematical model for this UAV was derived by using the Newton-Euler formalism, which captures the nonlinear and coupled dynamics of its six degrees of freedom. Six independent PD controllers were designed for regulating the translational motions (x, y, z) and the rotational motions (Φ, θ, ψ). In order to overcome the limitations of classical tuning, four meta-heuristic algorithms (the Invasive Weed Optimization (IWO) algorithm, Ant Colony Optimization (ACO) algorithm, Cultural Algorithm (CA) and Black Hole Algorithm (BHA)) were employed for optimally tuning the PD controller gains. Further on, the proposed control strategy was validated for two trajectory tracking scenarios which represent typical UAV navigation tasks. Additionally, robustness tests were conducted under external disturbances for evaluating the stability and disturbance rejection performance of the coaxial birotor UAV. Also, comparative simulations were carried out for assessing the tracking error (mean squared error), overshoot, and settling time for the analysed UAV, demonstrating that meta-heuristic-based tuning considerably improved the accuracy, robustness, and dynamic response in comparison with the conventional methods. The obtained results highlight the effectiveness of intelligent optimization for enhancing UAV control, particularly for a precise and stable trajectory.

Keywords

UAV, Coaxial Birotor, ACO, CA, IWO, BHA, Nonlinear control system, Trajectory Tracking, PID/PD.

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