Abstract
In order to improve the reliability and braking torque of aircraft electric braking system, this paper selected switched reluctance motor (SRM) as drive motor of electromechanical actuator, static torque data of SRM calculated by finite element analysis were used as training samples, then characteristics of torque-angle were obtained off-line by Generalized Regression Neural Network with particle swarm optimization (PSO-GRNN), and the nonlinear mapping from the torque to current was completed, torque inverse model is obtained which has large effects on the control performance of Instantaneous torque control, finally combining the torque sharing function (TSF) to constitute the torque control system of SRM. Simulation and experiment are proved: the system has good dynamic performance, and it can quickly and accurately track the expected braking torque.
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