Active Disturbance Rejection Tracking Control for Variable‐Load Quadrotor via PSO Algorithm‐Based Parameters Adaptation

ABSTRACT

Quadrotors with variable payloads face significant challenges in maintaining flight stability due to dynamic uncertainties and external disturbances. Existing control methods often lack adaptive parameter tuning mechanisms, leading to degraded performance under varying loads. This paper proposes an optimized active disturbance rejection control (ADRC) strategy based on particle swarm optimization (PSO) to achieve robust trajectory tracking while adapting to load changes. Firstly, a quadrotor model subject to variable load is constructed to describe significant changes in dynamic performance. Secondly, in a cascade control scheme, a tracking differentiator is presented to alleviate overshoot and track speed, while an extended state observer is given for estimating the total disturbance. Moreover, by means of uncertain compensation, the active disturbance rejection control schemes are developed for the position and attitude control loops, respectively. Thirdly, to tune a large number of parameters, a particle swarm optimization algorithm is introduced to achieve parameter adaptation. Finally, numerical examples are provided to illustrate the advantages and effectiveness of the proposed approaches in terms of flight stability, robustness, and parameter adaptivity.