Design of PD-type second-order ILC law for PMSM servo position control

Abstract

Abstract An iterative learning control method is better to control the high-order nonlinear strong coupling and external disturbances in the permanent magnet synchronous motor position servo system. This paper proposes a second-order P.D. type iterative learning control strategy, which can effectively achieve the optimal tracking control algorithm. By using the generalization of the Young inequality of convolution, the Lebesgue-p norm is obtained under the adequate condition that the tracking error converges monotonously. Furthermore, the convergence rate of second-order iterative learning control is compared, and it is proved by the mathematical knowledge that second-order iterative learning control is much better than a first-order iterative learning control under satisfactory conditions. Simulation results show that the effectiveness of the proposed algorithm is better than that of the traditional method, and the error of the iterative learning control strategy is smaller but with higher accuracy.