Design of Adaptive Intelligent Controllers for Switched Reluctance Motor Drives

• Main Authors: Shao-Chuan Chien, 簡劭全
• Other Authors: 王順源
• Format: Others
• Language: zh-TW
• Published: 2013
• Online Access: http://ndltd.ncl.edu.tw/handle/5628p4

博士 === 國立臺北科技大學 === 電機工程系博士班 === 101 === In this dissertation, intelligent control techniques are utilized to design the speed controllers and implement an intelligent control drive for switched reluctance motors (SRMs). The proposed control schemes are able to provide high-performance solutions for SRM drives. SRMs have many advantages such as high torque output, high efficiency, no rotor windings, and low cost. However, the doubly salient-pole structure on both the stator and the rotor leads to the high nonlinearity of torque output and makes SRMs difficult to control. Since both the TSK-fuzzy controller and the fuzzy cerebellar model articulation controller (FCMAC) provide good capability to deal with nonlinearity, the both two intelligent control techniques are adopted to design high-performance speed controllers for SRM drives in this research. The parameters of the proposed controllers are self-tuning according to the adaptation laws derived by Lyapunov theory. Hence, the proposed controllers could not only demonstrate superior performance in a wide speed range, but also exhibit good robustness in the face of motor parameter variation and external load disturbance rejection. To verify the performance and feasibility of the controllers, a dSPACE-DS1104 digital signal processing platform is utilized to implement the proposed control schemes. From the experimental results, it could be seen clearly that the dynamic performance and the robustness against load disturbance of the SRM drive are both outstanding.