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Go to Editorial ManagerIn this paper induction motor and its direct torque control are simulated and a speed estimator scheme based on wavenet (WN) theory has been developed and compared with the actual speed. The wavenet speed estimator inputs are a single line current and the state of the torque comparator output which are trained to follow the relationship between the motor current and the rotor speed. To ensure the validity of this scheme, the estimated speed is compared with a speed estimated from a conventional model reference adaptive system (MRAS). The operation of direct torque control (DTC) drive with the actual speed and the estimated wavenet speed as a feedback signal are simulated and compared. The results show that the wavenet method is effective for rotor speed estimation.
An intelligent and anticipatory speed controller for internal combustion engines was designed theoretically and examined experimentally. This design was based on the addition of a torque loop to the main speed loop. The model can sense the external load with the help of a load cell and send this signal to a soft computing unit for analysis and processing. This scheme will improve the ability of anticipation of controller since it treats the factors that affect the speed, not the speed itself. The experimental design was implemented using two types of actuating techniques; an intelligent throttling actuator and an intelligent injection actuator. The signal was analyzed by using intelligent techniques such as fuzzy logic, neural network and genetic algorithm. The experimental data were used to train the neural and the Adaptive Neuro–Fuzzy Inference System. The comparison of the results obtained in this work with other available models proved the efficiency and the robustness of the present model.