Title :
A comparison of training algorithms for DHP adaptive critic neurocontrol
Author :
Lendaris, George G. ; Shannon, Thaddeus T. ; Rustan, Andres
Author_Institution :
Dept. of Electr. & Comput. Eng., Portland State Univ., OR, USA
Abstract :
A variety of alternate training strategies for implementing the dual heuristic programming (DHP) method of approximate dynamic programming in the neurocontrol context are explored. The DHP method of controller training has been successfully demonstrated by a number of authors on a variety of control problems in recent years, but no unified view of the implementation details of the method has yet emerged. A number of options are described for sequencing the training of the controller and critic networks in DHP implementations. Results are given about their relative efficiency and the quality of the resulting controllers for two benchmark control problems
Keywords :
adaptive control; dynamic programming; heuristic programming; learning (artificial intelligence); neurocontrollers; adaptive control; approximate dynamic programming; critic neural networks; dual heuristic programming; learning algorithms; neurocontrol; sequencing; Amorphous materials; Design methodology; Design optimization; Dynamic programming; Equations; Feedback loop; Neural networks; Process design; Shape control; Supervised learning;
Conference_Titel :
Neural Networks, 1999. IJCNN '99. International Joint Conference on
Conference_Location :
Washington, DC
Print_ISBN :
0-7803-5529-6
DOI :
10.1109/IJCNN.1999.833415
