Fast iterative position estimation method of permanent magnet synchronous linear motor

Abstract In this paper, a Fast Iterative Phase Estimation (FIPE) algorithm is proposed for robotic grinding force control devices using Permanent Magnet Synchronous Linear Motors (PMSLM), requiring high positional accuracy and response speed. FIPE obtains optimal phase estimates through iterative searching and exhibit excellent dynamic performance. The proposed method is optimized by iterative optimization algorithms, which significantly reduces the number of iterations and enhance the response speed of position estimation. In addition, the effects of harmonics, amplitude mismatch, noise and DC errors in the raw signal on the FIPE algorithm are discussed, and a shallow neural network is introduced to compensate the periodic errors. The experimental results show that the FIPE algorithm has higher calculation accuracy and dynamic performance than the traditional PLL such as SRF-PLL, ANF-PLL and LKF-PLL, and has faster iteration speed than the traditional position estimator such as FPS-PLL.