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This paper propose about using PID control system based on Kp, Ki, and Kd parameter determination with scheduling process from fuzzy logic. Control system is used to arrange speed of three phase induction motor using IFOC method. This method can be minimized the main problem from speed control of induction motor which is a transient condition. The robustness validation from this system use testing process of dynamic speed which is compared with the other control system to know the system performance in transient condition such as (rise time, overshoot, undershoot and settling time). The result shows using the proposed system has better performance responses which is requiring 0.001 seconds time in transient condition up to steady state condition without overshoot and undershoot problem.

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AhshactFrequency stability is a part of the power iystem reliability. To overcome drastically decreasing frequency of the system, usually, load shedding is performed. Automatic load shedding is required to anticipate and enhance the time response. The trained neural network is an alternative method for solving a kind of problems.KEYWORDS : .adaptive load shedding. frequeocy control, neural network . 0-7803-7490-8/02/$17.00Q2002 IEEE.17' 78

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The operation of induction motors with high performance contributes significantly to the global energy savings but hysteresis loss is one of the factors causing decreased performance. Stator flux density (B) and magnetic field intensity (H) must be plotted to know hysteresis loss quantity. Unfortunately, since the rotor rotates in time series, the stator flux density is unmeasurable quantities. It is hard to directly detect this properties because of limited airgap space and costly installation of additional instrument The purpose of this paper is to evaluate the hysteresis loss quantity in induction motor using a novel method of multilayer perceptron Feed Forward Neural Network (FFNN) as stator flux estimator and magnetizing current model as magnetic field intensity properties. This method is effective because it's non-destructive method, without an additional instrument, low cost, and suitable for real-time motor drive systems. The FFNN estimator response is satisfied because it is accurate to estimate stator flux density for evaluating hysteresis loss quantity including its magnitude and phase angle. By using the proposed model, the stator flux density and magnetizing current can be plotted to be hysteresis loss curve. The performance of flux response, speed response, torque response and error deviation of stator flux estimator has been presented, investigated, compared and verified in Simulink Matlab.

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