Position sensorless positioning servo system based on feedback error learning

This paper proposes a novel position sensorless positioning servo system using feedback error learning (FEL). Recently, a position sensorless positioning servo system of interior permanent magnet synchronous motors (IPMSMs) has been studied for realizing the high reliability and cost reduction. For the fast response of positioning servo systems, accurate parameters of IPMSMs are required. However, the parameters vary due to temperature and/or aging, which causes degradation of the positioning control performance. Thus, this paper proposes a novel position-sensorless positioning servo system for IPMSMs using the FEL algorithm for motor parameters identification. Besides, this paper employs the comb filters, which is well known as the fast rotor position estimation method. Experiments are demonstrated to validate the effectiveness and feasibility of the proposed method.