Adaptive Fuzzy Active-Disturbance Rejection Control-Based Reconfiguration Controller Design for Aircraft Anti-Skid Braking System
Zhao Zhang,
Zhong Yang,
Guoxing Zhou,
Shuchang Liu,
Dongsheng Zhou,
Shuang Chen,
Xiaokai Zhang
Affiliations
Zhao Zhang
College of Automation Engineering, Nanjing University of Aeronautics and Astronautics, Nanjing 211106, China
Zhong Yang
College of Automation Engineering, Nanjing University of Aeronautics and Astronautics, Nanjing 211106, China
Guoxing Zhou
Research Institute of UAV, Nanjing University of Aeronautics and Astronautics, Nanjing 211106, China
Shuchang Liu
College of Automation Engineering, Nanjing University of Aeronautics and Astronautics, Nanjing 211106, China
Dongsheng Zhou
College of Automation Engineering, Nanjing University of Aeronautics and Astronautics, Nanjing 211106, China
Shuang Chen
Electronic Engineering Department, Aviation Key Laboratory of Science and Technology on Aero Electromechanical System Integration, Nanjing 211106, China
Xiaokai Zhang
Electronic Engineering Department, Aviation Key Laboratory of Science and Technology on Aero Electromechanical System Integration, Nanjing 211106, China
The aircraft anti-skid braking system (AABS) is an essential aero electromechanical system to ensure safe take-off, landing, and taxiing of aircraft. In addition to the strong nonlinearity, strong coupling, and time-varying parameters in aircraft dynamics, the faults of actuators, sensors, and other components can also seriously affect the safety and reliability of AABS. In this paper, a reconfiguration controller-based adaptive fuzzy active-disturbance rejection control (AFADRC) is proposed for AABS to meet increased performance demands in fault-perturbed conditions as well as those concerning reliability and safety requirements. The developed controller takes component faults, external disturbance, and measurement noise as the total perturbations, which are estimated by an adaptive extended state observer (AESO). The nonlinear state error feedback (NLSEF) combined with fuzzy logic can compensate for the adverse effects and ensure that the faulty AABS maintains acceptable performance. Numerical simulations are carried out in different runway environments. The results validate the robustness and reconfiguration control capability of the proposed method, which improves AABS safety as well as braking efficiency.
