Dynamic identification and control of PWM inverter VAr compensator using neural network

Author

Hosseini, S.H. ; Tonekaboni, S.H.

Author_Institution

Dept. of Electr. Eng., Tabriz Univ., Iran

fYear

1999

Firstpage

268

Abstract

The performance and dynamic characteristic of a solid-state VAr compensator controlled by a neural network is presented and analyzed. Neural network based indirect model reference adaptive control (NN-MRAC) theory is used to design the multioutput nonlinear controller structure. Simulation results of the closed loop control system using a multioutput nonlinear neural network controller demonstrate desirable reactive power compensation and voltage regulation.

Keywords

DC-AC power convertors; PWM invertors; closed loop systems; control system analysis; control system synthesis; model reference adaptive control systems; neurocontrollers; nonlinear control systems; power system control; reactive power control; voltage control; PWM inverter; closed loop control system; control design; control simulation; dynamic characteristic; indirect model reference adaptive neurocontrol; multioutput nonlinear controller structure; reactive power compensation; solid-state VAr compensator; voltage regulation; Adaptive control; Neural networks; Nonlinear control systems; Nonlinear dynamical systems; Performance analysis; Power system modeling; Pulse width modulation inverters; Reactive power; Solid state circuits; Voltage control;

fLanguage

English

Publisher

ieee

Conference_Titel

Electric Power Engineering, 1999. PowerTech Budapest 99. International Conference on

Conference_Location

Budapest, Hungary

Print_ISBN

0-7803-5836-8

Type

conf

DOI

10.1109/PTC.1999.826700

Filename

826700