TY - GEN
T1 - Excitation control system based on multi-objective Heuristic Dynamic Programming
AU - Lin, Yuzhang
PY - 2011
Y1 - 2011
N2 - A multi-objective adaptive dynamic programming method is proposed in this paper to solve the optimal control with multi-objective performance indices. The multi-objective performance indices are commonly used in engineering fields. In the paper, vector-valued performance indices are transformed into a scalar by vector's 2-norm. Multi-objective adaptive dynamic programming is derived from adaptive critic design and neural network. Heuristic Dynamic Programming (HDP) is a member of Adaptive Dynamic Programming. This method is implemented with Neural Network, so it does not require an accurate model of the plant. The dynamics of the system is learned from the history data, and from the data of real time control process. The proposed method updates the controller's parameters periodically, so the control law can be updated with the change of environment. It solves the problem step by step and optimizes the multi-objective performance indices in real time. The simulation shows the effectiveness of the method in the excitation control of synchronous generators.
AB - A multi-objective adaptive dynamic programming method is proposed in this paper to solve the optimal control with multi-objective performance indices. The multi-objective performance indices are commonly used in engineering fields. In the paper, vector-valued performance indices are transformed into a scalar by vector's 2-norm. Multi-objective adaptive dynamic programming is derived from adaptive critic design and neural network. Heuristic Dynamic Programming (HDP) is a member of Adaptive Dynamic Programming. This method is implemented with Neural Network, so it does not require an accurate model of the plant. The dynamics of the system is learned from the history data, and from the data of real time control process. The proposed method updates the controller's parameters periodically, so the control law can be updated with the change of environment. It solves the problem step by step and optimizes the multi-objective performance indices in real time. The simulation shows the effectiveness of the method in the excitation control of synchronous generators.
KW - Adaptive Dynamic Programming (ADP)
KW - Heuristic Dynamic Programming (HDP)
KW - excitation system
KW - multi-objective
KW - neural network
KW - synchronous generator
UR - http://www.scopus.com/inward/record.url?scp=84863147701&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=84863147701&partnerID=8YFLogxK
U2 - 10.1109/PEAM.2011.6134958
DO - 10.1109/PEAM.2011.6134958
M3 - Conference contribution
AN - SCOPUS:84863147701
SN - 9781424496884
T3 - PEAM 2011 - Proceedings: 2011 IEEE Power Engineering and Automation Conference
SP - 348
EP - 353
BT - PEAM 2011 - Proceedings
T2 - 2011 IEEE Power Engineering and Automation Conference, PEAM 2011
Y2 - 8 September 2011 through 9 September 2011
ER -