Design and Implementation of Model-Based Predictive Controllers for Synchronous Reluctance Motor Drive Systems

• Main Authors: NUR VIDIA LAKSMI B., 巴偉地
• Other Authors: Tian-Hua Liu
• Format: Others
• Language: en_US
• Published: 2018
• Online Access: http://ndltd.ncl.edu.tw/handle/5xnv7p

碩士 === 國立臺灣科技大學 === 電機工程系 === 106 === Synchronous Reluctance Motor (SynRM) has drawn great attention due to its simple structure, good robustness, and no permanent magnet material. This thesis proposes a systematic design and implementation of a model-based predictive speed controller and current controller for SynRM drive systems. The model-based predictive controllers require motor parameters such as resistance, inductance, and back EMF. Although the parameters are varying every sampling interval, the proposed controllers can adapt well due to the augmented state variables and constraints. As a result, the proposed controllers improve dynamic responses of the drive system, including transient responses, load disturbance responses, and tracking responses. In addition, a minimized cost function is used to determine the switching states of each sampling interval. To demonstrate the performance, a three-phase, 560 W SynRM drive system is implemented to provide a wide adjustable speed range, from 2 r/min to 1800 r/min. A 32-bit floating-point TMS-320-F-28335 DSP is used to execute the control algorithms. As a result, the hardware is very simple. Experimental results show that the model-based predictive controllers have better performance than the PI controller. The parameters of the PI controller are determined by pole assignment technique.