Mengsha, Mamo (PhD)Biniam, Abera2020-12-052023-11-282020-12-052023-11-282020-06http://etd.aau.edu.et/handle/12345678/23856This thesis presents design and simulation of Artificial Neural Network solution for speed estimation including an ANFIS for control of IM drives. In the past years the research efforts in the field of IM control concentrated on the identification and observation of this highly nonlinear dynamic plant. Existing vector control methods require speed sensor for control and field orientation purpose, but their installation makes the drive system bulky, unreliable and expensive and installing them might not be feasible in some applications, such as motor drives in hostile environment or high-speed drives. In such cases speed is obtained from easily measurable stator quantities. Many speed sensorless techniques have been proposed to cope up with speed sensing problem. Developed speed estimation algorithms are more or less parameter dependent and/ or computationally time consuming. In this thesis, the proposed estimation method is based on ANN to obtain the speed signal. The conventional PI controller is replaced by an ANFIS which tunes the fuzzy inference system with hybrid learning algorithm. The ANN is used as estimator, trained by Levenberg- Marquardit algorithm. The data for training are obtained from conventional FOC simulations when the motor drive is working in closed loop at various values of speeds and loads for speed observation. The complete drive system is modeled using MATLAB®2019a. Finally, the drive results have been analyzed for both steady state and dynamic conditions such as of speed tracking capability, torque response quickness, low speed behavior, step response of drive with speed reversal and sensitivity to motor parameter uncertainty. The error of simulation result between actual and estimated speed have been less than 0.3% for transient response, 0.2% for speed tracking and 0.44% during low speed operation. It was observed from simulation results that by using PI and ANFIS controller, for the reference speed of 151rad/sec, the rise and settling time are improved by 0.0938 and 0.1289 seconds at full respectively also robust response is achieved with the latter controller.en-USField Oriented ControlSVPWMSpeed Sensorless OperationANNANFISThesis