ONLINE ADAPTIVE ARTIFICIAL NEURAL-NETWORK-BASED VECTOR CONTROL OF PERMANENT-MAGNET SYNCHRONOUS MOTORS

This paper presents a novel approach of speed control for a permanent magnet synchronous motor (PMSM) using on-line self tuning artificial n eural network (ANN). Based on motor dynamics and non-linear load chara cteristics, an ANN speed controller is developed and integrated with t he vector control scheme of the PMSM drive. The combined use of off-li ne and on-line weights and biases adjustments offers a unique feature of on-line system identification and precise speed control of a high p erformance PMSM drive. The complete drive system is implemented in rea l time using a digital signal processor controller board-DS1102 on a l aboratory 1 hp PMSM. using the experimental setup, the performances of the proposed drive system are evaluated under various operating condi tions. The test results validate the efficacy of the ANN for precise s peed control of the PMSM drive. Furthermore, the use of ANN makes the drive system robust, accurate and insensitive to parameter variations.