Event-Triggered Fault-Tolerant ADRC for Variable-Load Quadrotor with Prescribed Performance - Zhichen Li; Qiaoran Wang; Huaicheng Yan (Applied Sciences)
This study proposes an event-triggered fault-tolerant active disturbance rejection control (ADRC) method for variable-load quadrotors with prescribed performance. The quadrotor, as a nonlinear and underactuated system, faces challenges such as payload variations, actuator faults, and external disturbances, which degrade trajectory tracking accuracy and stability. The proposed approach integrates a cascaded ADRC framework, decoupling the system into position and velocity subsystems, each equipped with extended state observers (ESOs) for real-time disturbance estimation and compensation. To enhance robustness, prescribed performance functions dynamically constrain tracking errors within predefined bounds, while event-triggered mechanisms reduce computational load through condition-based updates of control signals. Additionally, a particle swarm optimization (PSO) algorithm is employed for online parameter tuning, improving adaptability. Theoretical analysis confirms the system stability, and simulation results demonstrate the controller effectiveness in handling actuator faults and variable payloads, ensuring accurate trajectory tracking and reduced resource consumption. The method offers a promising solution for robust and efficient quadrotor control in complex environments.