Title :
Genetic algorithms for control of power converters
Author :
Schutten, Michael J. ; Torrey, David A.
Author_Institution :
Gen. Electr. Corp. Res. & Dev. Center, Schenectady, NY, USA
Abstract :
This paper evaluates genetic algorithms (GAs) as a new nonlinear technique for the control of power converters. Genetic algorithms are a class of parallel processing learning techniques. They are used to optimize power converter control laws relative to a performance index. An example using a full-bridge topology verifies the usefulness of this technique
Keywords :
bridge circuits; circuit analysis computing; control system analysis computing; digital simulation; genetic algorithms; nonlinear control systems; optimal control; power convertors; power engineering computing; voltage control; computer simulation; control laws; full-bridge topology; genetic algorithms; learning techniques; nonlinear control; parallel processing; performance index; power converters; voltage regulation; Aggregates; Biological cells; Cost function; Genetic algorithms; Genetic mutations; Power semiconductor switches; Reactive power; Resonance; Switching converters; Topology;
Conference_Titel :
Power Electronics Specialists Conference, 1995. PESC '95 Record., 26th Annual IEEE
Conference_Location :
Atlanta, GA
Print_ISBN :
0-7803-2730-6
DOI :
10.1109/PESC.1995.474985
