Abstract
The current research develops a mathematical model and control strategies to address two major problems force fighting and precise position tracking for a hybrid actuation system composed of servo-hydraulic actuator and electro-mechanical actuator (SHA/EMA). The force fighting and desired position tracking are two essential problems of the SHA/EMA actuation system for a large civil aircraft. The trajectory-based fractional order proportional integral derivative (FOPID) control for the SHA/EMA actuation system is proposed, tuned with the help of the particle swarm optimization (PSO) technique and implemented with the support of the FOMCON toolbox in Matlab. The experiments are performed under different external aerodynamic loads that the aircraft usually experiences during flight operations. The results show that the proposed method shows better results for tracking performance, force fighting and load rejection ability.
Highlights
In more electric aircraft (MEA), we try to reduce the hydraulic components and replace them with electrical components
In Boeing 787, five electromechanical actuators (EMA) are involved, four EMA are used for spoilers and one EMA is used for trim horizontal stabilizer (THS)
The research work focuses on reducing force fighting and improving the position tracking performance of the control surface for the servo-hydraulic actuator and electro-mechanical actuator (SHA/EMA) actuation system of a prominent civil aircraft
Summary
In more electric aircraft (MEA), we try to reduce the hydraulic components and replace them with electrical components. The precision and tracking accuracy can be increased by considering the external disturbances nonlinear dynamics, and the coupling effect in the hybrid actuation system Several authors tried their best to solve the problem of force fighting and position tracking for the redundant actuation system (the hybrid actuation system). In [13,14], an intelligent controller is designed using fuzzy logic to address the problem of force fighting and position tracking for the HA/EHA system Adaptive control techniques, such as the MIT rule and model reference control, are employed to synchronize the motion between HA and EHA [15,16]. An author presented an adaptive decoupling controller that eliminates coupling terms to reduce force fighting and improve position tracking performance for the HA/EHA actuation system [26]. The main paper contents are modelling of the SHA/EMA system, controller design through machine learning techniques, and the results and discussion part are followed by conclusions
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