Tutku Buyukdegirmenci with adviser P. T. Krein This research goal is to obtain robust and well-conditioned induction machine operation under parameter uncertainties. Direct torque control (DTC), compared to other high performance induction machine control algorithms, has the least amount of parameter dependency. However, in the past few decades practitioners have reported erratic behavior under high-speed […]
A Comparative Study of an Exponential Adaptive Perturb and Observe Algorithm and Ripple Correlation Control for Real-Time Optimization
Veysel (Tutku) Buyukdegirmenci with Ali Bazzi and adviser P. T. Krein This project develops an algorithm to optimize real-time problems where ripple correlation control (RCC) cannot be utilized because the given applications have no inherent ripple. Real-time optimization tracks the cost function optimum in a dynamic system. Known techniques for real-time optimization are perturb and […]
Comprehensive and Practical Optimization for Point-of-Load Voltage Regulator Design
Yingying Kuai with adviser P. L. Chapman This project develops a comprehensive and practical optimization solution for a complete multi-phase voltage regulator module (VRM) system. Early work in power electronics optimization assumed continuous variable space. This leads to solutions unsuitable for immediate implementation, as, in reality, many parameters are discrete. Dynamic voltage regulation during fast […]
Real-Time Loss Minimization in Induction Machines
Ali M. Bazzi with adviser P. T. Krein Loss minimization in induction machines was reviewed and loss minimization techniques (LMTs) were categorized and compared. Model-based, physics-based, and hybrid LMTs can all minimize power losses in an induction machine but have different characteristics. Model-based techniques are model-dependent and thus sensitive to errors or variations in machine […]