Optimized Control of a Brushless Doubly Fed Reluctance Motor using a Sliding Mode Controller

Abstract

Brushless Doubly Fed Reluctance Machines (BDFRMs) have emerged as strong candidates for limited accessibility and sustainable applications such as wind energy conversion systems and variable speed pump drives due to their characteristic advantages such as low maintenance, reduced converter cost, and independence from rare earth magnets. However, the complex nonlinear characteristics of BDFRMs, coupled with the presence of significant current and flux harmonics, make high performance current control particularly challenging. This thesis proposes the use of a Discrete Time Super Twisting Sliding Mode (DTSTSM) controller under a Field Oriented Control (FOC) framework to address these issues. The DTSTSM controller provides fast dynamic response, improved robustness, and reduced chattering, which are crucial for nonlinear systems like BDFRMs. To ensure optimal performance, the controller parameters are tuned automatically using a Particle Swarm Optimization (PSO) algorithm. A detailed harmonic analysis of the BDFRM is carried out to study the influence of its inherent nonlinearity on control performance. Experimental validation is conducted using a conventional PI controller for comparison. The results demonstrate that the proposed DTSTSM controller strategy significantly improves current tracking accuracy and dynamic response while maintaining stability under varying operating conditions. This work contributes to the ongoing development of effective control strategies for BDFRMs and promotes their use in clean energy generation and consumption sectors.