A two-stage robust-intelligent controller design for efficient LFC based on Kharitonov theorem and fuzzy logic

This paper proposes an efficient load frequency control (LFC) approach based on robust and intelligent methods. Practically speaking, proportional-integral (PI) controller is widely deployed in LFC structure. Basically, the parameters of PI controller are adjusted based on trial-and-error or classic control methods. In such manners, robust performance of PI controller cannot be guaranteed in disturbances including load changes or parameter variations. In this research, at the first stage, the gain values of PI controller are tuned in an offline manner based on Kharitonov theorem which strengthens the validity of the controller against the variations in time constants of turbine and governor. As another aspect of uncertainty, power system loading demand is changed ceaselessly. To accommodate such conditions, at the second stage, the initial gain values based on Kharitonov theorem are adapted in an online manner based on fuzzy logic approach. The fuzzy controller, as an aspect of intelligence, adapts the proportional and integral gains through appropriate membership functions in an online fashion. Frequency deviation and its derivative are selected as efficient input signals for the fuzzy controller. Detailed numerical studies are conducted to assess performance of the proposed approach. Results demonstrate a reliable frequency performance against different uncertainties.