关键词: 高速无人机, 全电刹车, 摩擦系数预测, 分级PID控制, 刹车惯性台试验

Abstract: To address the strong nonlinearity, high coupling, and time-varying parameters of unmanned aerial vehicle (UAV) all-electric braking systems, this paper proposes a hierarchical PID control strategy. The control parameters are adjusted in different stages according to the slip ratio to improve the aircraft's deceleration performance. First, models of aircraft ground taxiing, wheel dynamics, tire-runway friction, and all-electric actuators were developed in Simulink. Futhermore, a predictive model for the brake disc friction coefficient was established using a genetic algorithm (GA)-optimized BP neural network, accounting for its real-time variations with temperature and braking pressure. A hierarchical PID control system comprising baseline braking, dynamic adjustment braking, and anti-skid braking was then designed. Through simulation analysis, a comparative study was conducted on the control performance of PD+PBM control and hierarchical PID control. Experimental verification of the hierarchical PID control strategy was also carried out on a ground inertia test bench. The results demonstrate that the proposed hierarchical PID method achieves superior control performance. The error between simulation and experimental results is within 11%, validating both the correctness of the simulation model and the effectiveness of the control strategy. The hierarchical PID controller exhibits satisfactory performance, enabling the aircraft to attain high deceleration rates under various operating conditions. Even under the most extreme and adverse condition—a wet runway with wet brake disks—the average deceleration rate of the aircraft in both simulation and experiments exceeds 2 m/s2, with an error between them within 5.58%.

Key words: High-speed UAV, All-electric braking, Friction coefficient prediction, Hierarchical PID control, Brake inertia bench