Asenkron motorların sargı arası kısa devre arızası tespit özelliği ile zenginleştirilmiş model öngörülü moment denetimi

Model predictive control (MPC) is a popular research topic in modern power electronics and it has been applied to a large variety of power converters and electric drives. The reason behind this interest in MPC is the advantages that it offers: intuitive and flexible algorithm, fast dynamic response, ease of handling converter nonlinearities, and system constraints, to name a few. In this thesis, MPC is applied to the torque control of an induction motor (IM). Involving both the theoretical foundation, computer simulations and experimental implementation, MPC of IM has been thoroughly documented. Detailed laboratory results suggest a good motor drive performance. Further issues regarding MPC, such as weighting factor tuning, computation time, and the dynamically varied weighting factor, are also examined. A novel algorithm that runs as an add-on to the predictive controller is developed to detect and locate inter-turn short circuit (ITSC) faults for the IM. ITSC faults are a severe fault type that needs quick identification or else it leads to the complete malfunctioning of the machine. It is observed that an effective controller inherently tries to compensate for the fault's corrupting influence, hence covers the fault signatures. Therefore, it is vital to address any fault detection technique in conjunction with the main controller, for a closed-loop controlled system. The basic principle utilized for fault detection is to observe the controller's outputs for any unexpected unbalance. The effectiveness of the proposed fault detection algorithm is verified with laborious experimental data. The fault and the drive system's interaction is examined with various aspects, such as the fault's effect on the cost function, current prediction error, and high-frequency impedance of the machine. Additionally, a new simulation model for the IM with ITSC fault is developed, the effectiveness of which is also verified through experimental results.