Robust H2-PSS design based on LQG control optimized by genetic algorithms

Abstract

This paper proposes a genetic algorithms (GA) optimization technique applied to power system stabilizer (PSS) for adapt a robust H2 control based on linear quadratic controller (LQ) and Kalman Filter applied on automatic excitation control of powerful synchronous generators, to improve stability and robustness of power system type single machine connected to an infinite bus system (SMIB). Adaptation technique proposed of the robust H2 control with the various electrical and mechanical parametric variations based on the optimization of the PSS parameters. The genetic algorithms is a search technique based on the mechanisms of natural selection of a genetic and evolution. This optimization technique is more used in the field of control for solve optimal choice problem of regulators parameters. The integration of GA to robust H2 control with robustness test (electrical and mechanical parameters variations of the synchronous machine) show considerable improvements in dynamics performances, robustness stability and good adaptation of the robust H2-PSS parameters under uncertain constraints. This present study was performed using our realized Graphical User Interface (GUI) developed under MATLAB.