RBF Neural Network Based Correction Iterative Learning Control for Direct-drive Pump-controlled Clutch Actuator

Abstract

This paper mainly focuses on the motion control of a novel direct-drive pump-controlled clutch-actuator system. The RBF neural network and iterative learning control method are combined to perform fast and accurate position tracking for dynamic nonlinear systems with high uncertainty. And the simulink and AMEsim co-simulation is carried out under different conditions. The simulation results confirm that the proposed RBF neural network based correction ILC controller has sufficient practicability and is suitable for the direct-drive pump-controlled actuator motion control conditions.