An adaptive control method for the linear switched reluctance motor based on DSP

Abstract

The linear switched reluctance motor (LSRM) is a new kind of direct-drive actuator, however, it is very difficult to build an exact theoretic model for the LSRM. In this paper, an indirect self-tuner is proposed for position control of the LSRM by combining the recursive least squares (RLS) estimator with the minimum-degree pole placement method (MDPP) for controller design. Control system construction and operation based on one single Digital Signal Processor (DSP) are also established. Experimental results demonstrate the control scheme with on-line least-square parameter identification has a better performance than PID controller on modifying steady-error variances between each operation side in square-wave tracking. Experimental results prove that the control algorithm considering disturbances has smaller steady-state error compared with PID control algorithm.