Dry clutch control is a typical nonlinear problem due to the nonlinear characteristics of diaphragm springs. For precise position control of the automated dry clutch, a modified predictive functional control (mPFC) method is proposed. First, a novel mechanical actuator is designed and models of the automated dry clutch system are built based on theoretical analysis and experimental data. Then, in order to compensate for the position error of direct current (DC) motor caused by load torque, modifications are introduced to a regular predictive functional control (PFC), including a sliding mode observer (SMO) to estimate the load torque and a predictive model concerning the load torque. Next, simulations show that the SMO could estimate the load torque accurately and the mPFC performs well with the nonlinear load torque. Finally, experiments are carried out on a test bench and the results are in accordance with the simulations. Due to the little online computing burden and the simple structure of the mPFC, it could be used in other industrial control systems which need fast response.
Iterative sliding mode observer for sensorless control of five-phase permanent magnet synchronous motor
