Title :
A nural network indentification method for the inverter
Author_Institution :
Wuhan Univ., Wuhan
Abstract :
The paper investigates the use of neural networks for identification of power converter. A nonparametric model of the AC-to-DC inverter implemented by means of a neural network identifies the inverter dynamics in cases of uncertainty in the input voltage supply and/or load parameter. The circuit consists of a main circuit, control system, together with the source inductance and the output filter. The ultimate object is used in the analysis of power system. Simulation results in a PWM inverter under large-signal operation illustrate the applications and detect the characteristics of the circuit.
Keywords :
AC-DC power convertors; PWM invertors; PWM power convertors; neural nets; power engineering computing; AC-DC inverter; PWM inverter; neural network identification method; nonparametric model; power converter; power system analysis; Circuits; Control systems; Inductance; Neural networks; Power system dynamics; Power system modeling; Power system simulation; Pulse width modulation inverters; Uncertainty; Voltage;
Conference_Titel :
Electrical Machines and Systems, 2008. ICEMS 2008. International Conference on
Conference_Location :
Wuhan
Print_ISBN :
978-1-4244-3826-6
Electronic_ISBN :
978-7-5062-9221-4
