Hysteresis operator-based adaptive Kalman feedforward control for the scanning motion of hybrid reluctance actuators

The hybrid reluctance actuator (HRA) has achieved widespread application in scanning motion tasks. However, the nonlinear perturbations arising from position-dependent stiffness fluctuations, hysteresis, eddy, and flux leakage can significantly affect the control performance. To enhance the control performance of HRA-based systems in scanning motion, this paper introduces an adaptive feedforward method, known as the Chua operator-based Kalman feedforward compensator (COKFC), which aims to mitigate these nonlinear perturbations, with a PID controller serving as the central control element. In the COKFC approach, a Chua operator is employed to effectively capture the inverse hysteresis behavior. A Chua-based time-varying feedforward compensation model is then formulated to represent the inversion of the nonlinear perturbations inherent in the HRA. An improved Kalman filter is utilized for the real-time adaptation of the time-varying parameters within the feedforward compensation model. The design procedure for this control strategy is presented. Experimental evaluations are conducted on an HRA-based stage (HRA-BS), and comparisons are made between the proposed method and several advanced control methods. The experimental results demonstrate that the proposed COKFC method exhibits superior control performance for the scanning motion of the HRA-BS, highlighting its effectiveness in practical applications.