Artificial neural networks for control of a grid-Connected rectifier/inverter under disturbance, dynamic and power converter switching conditions

IEEE Transactions on Neural Networks and Learning Systems

Volumn 25, Issue 4, 2014, Pages 738-750

  Li, Shuhui ^a   Fairbank, Michael ^b   Johnson, Cameron ^c   Wunsch, Donald C ^c   Alonso, Eduardo ^b   Proao, Julio L ^a  

^a University of Alabama   (United States)

^b CITY UNIVERSITY   (United Kingdom)

^c University of Missouri Rolla   (United States)

Author keywords

Backpropagation through time; Decoupled vector control; Dynamic programming; Grid connected rectifier inverter; Neural controller; Renewable energy conversion systems

Indexed keywords

CONTROLLERS; DYNAMIC PROGRAMMING; ELECTRIC POWER SYSTEMS; ENERGY CONVERSION; POWER CONVERTERS;

BACK-PROPAGATION THROUGH TIME; DECOUPLED VECTOR CONTROLS; GRID-CONNECTED RECTIFIER/INVERTER; NEURAL CONTROLLER; RENEWABLE ENERGY CONVERSION SYSTEMS;

NEURAL NETWORKS;

ALGORITHM; ARTIFICIAL NEURAL NETWORK; COMPUTER SIMULATION; DEVICE FAILURE ANALYSIS; DEVICES; ELECTRIC POWER PLANT; ELECTRICITY; ENERGY TRANSFER; EQUIPMENT DESIGN; FEEDBACK SYSTEM; POWER SUPPLY; SIGNAL PROCESSING; STATISTICAL MODEL;

ALGORITHMS; COMPUTER SIMULATION; ELECTRIC POWER SUPPLIES; ELECTRICITY; ENERGY TRANSFER; EQUIPMENT DESIGN; EQUIPMENT FAILURE ANALYSIS; FEEDBACK; MODELS, STATISTICAL; NEURAL NETWORKS (COMPUTER); POWER PLANTS; SIGNAL PROCESSING, COMPUTER-ASSISTED;

EID: 84897024197     PISSN: 2162237X     EISSN: 21622388     Source Type: Journal    
DOI: 10.1109/TNNLS.2013.2280906     Document Type: Article

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