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The main objective of Load Frequency Control (LFC) is to regulate the power output of the electric generator within an area in response to changes in system frequency and tie-line loading. Thus the LFC helps in maintaining the scheduled system frequency and tie-line power interchange with the other areas within the prescribed limits. Most LFCs are primarily composed of an integral controller. The integrator gain is set to a level that the compromises between fast transient recovery and low overshoot in the dynamic response of the overall system. This type of controller is slow and does not allow the controller designer to take in to account possible changes in operating condition and non-linearities in the generator unit. Moreover, it lacks in roubustness. Therefore the simple neural networks can alleviate this difficulty. The ANN is applied to self tune the parameters of PID controller. Multi area system, have been considered for simulation of the proposed self tuning ANN based PID controller. The performance of the PID type controller with fixed gain, Conventional integral controller, and ANN based PID controller have been compared through MATLAB Simulation results. Comparison of performance responses of integral controller & PID controller show that the neural-network controller has quite satisfactory generalization capability, feasibility and reliability, as well as accuracy in multi area system. The qualitative and quantitative comparison have been carried out for Integral, PID and ANN controllers. The superiority of the performance of ANN over integral and PID controller is highlighted.