Adaptive backstepping controller design for a matrix converter based PMSM drive system

This paper proposes a new control algorithm for a matrix converter based permanent-magnet synchronous motor (PMSM) position control system. First, a new switching strategy, which uses the neural-network learning technique, is proposed to reduce the current harmonics of the PMSM. Next, a nonlinear adaptive backstepping control algorithm is proposed to improve the system performance. By using the proposed controller, the system performs well. It has a good transient response, load disturbance rejection capability, and tracking ability. As a result, a satisfactory servo drive can be achieved. In addition, the realization of the controller is very simple. All the control loops, including current-loop, speed-loop, and position-loop, are implemented by a 32-bit TMS320C40 digital signal processor. The hardware, therefore, is very simple. Several experimental results are shown to validate the theoretical analysis.