Title :
An optimal adaptive power system stabilizer
Author :
Soos, Antal ; Malik, O.P.
Author_Institution :
Dept. of Electr. & Comput. Eng., Calgary Univ., Alta., Canada
Abstract :
An optimal control algorithm with adaptive system parameters and state variables estimation is presented in this paper. The optimal control algorithm is calculated by solving the algebraic Riccati equation of the linearized closed loop system model obtained by using an adaptive recursive least squares identification algorithm. The feedback control is achieved by recalculating the control sequence each sampling period. An application of the algorithm as a power system stabilizer is illustrated
Keywords :
Riccati equations; adaptive control; closed loop systems; control system analysis; control system synthesis; feedback; optimal control; parameter estimation; power system control; power system stability; state estimation; PSS; adaptive recursive least squares identification algorithm; adaptive system parameters estimation; algebraic Riccati equation; control design; control sequence recalculation; control simulation; feedback control; linearized closed loop system model; optimal adaptive power system stabilizer; sampling period; state variables estimation; Adaptive control; Adaptive systems; Closed loop systems; Least squares methods; Optimal control; Power system modeling; Power systems; Programmable control; Riccati equations; State estimation;
Conference_Titel :
Power Engineering Society Summer Meeting, 1999. IEEE
Conference_Location :
Edmonton, Alta.
Print_ISBN :
0-7803-5569-5
DOI :
10.1109/PESS.1999.787492
