Automatic Generation Control of Interconnected Power System Using Ann Technique Based on Μ–synthesis

This paper presents a nonlinear Artificial Neural Networks (ANN) controller based on μ–synthesis for Automatic Generation Control (AGC) of power systems. Power systems such as other industrial plants have some uncertainties and deviations due to multivariable operating conditions and load changes. For this reason, in the design of ANN controller the idea of μ synthesis theory is used. The motivation of using the μ–based robust controller for training the proposed controller is to take the large parametric uncertainties and modeling error into account in such a way that both the stability of the overall system and good performance have been achieved for all admissible uncertainties. The simulation results on a twoarea power system show that the proposed ANN controller is effective and gives good dynamic responses even in the presence of Generation Rate Constraints (GRC). In addition, it is superior to the conventional PI and μ–based robust controllers.