Dynamic Behavior and Stability Analysis of Automatic Voltage Regulator with Parameter Uncertainty

Abstract

This research article describes a novel optimization technique called simulink design optimization (SDO) to compute the optimal PID coefficients for an automatic voltage regulator (AVR). The time-domain performance of the proposed controller was analyzed using MATLAB/Simulation, and its performance was compared with that of water cycle algorithm, genetic algorithm, and local unimodal sampling algorithm-based PID controllers. The robustness of the proposed controller was verified by applying the disturbances to the generator field voltage and the amplifier parameter uncertainty. The studies presented in literature were discussed the AVR loop stability using the Bode plot which will not give the minimum stability margins. This study proposes a novel stability analysis called disk-based stability analysis to authenticate the stability of the AVR loop which is obtained by the classical analysis. This stability was compared with the proposed stability analysis. The MATLAB results reveal that the SDO-PID controller regulates the terminal voltage of the generator precisely, is more robust to parameter uncertainty, and is more stable than the other controllers. The maximum allowable parameter uncertainty of the amplifier model was identified as 102% of its nominal parameters. The stability margins are recognized as DGM = 10.40 dB and DPM = 56.50° for the AVR stability.