DocumentCode
328310
Title
A policy- and experience- driven neural network (PENN) and its application to SISO and MIMO process control
Author
Ishida, Masaru ; ZHAN, Jixian
Author_Institution
Res. Lab. of Resources Utilization, Tokyo Inst. of Technol., Yokohama, Japan
Volume
1
fYear
1993
fDate
25-29 Oct. 1993
Firstpage
681
Abstract
A policy- and experience- driven Neural Network (PENN) is proposed. Its applicability is confirmed by applying it to both a nonlinear SISO water-level control with and without time delay and a MIMO distillation control. By online learning of both the global policy and local experience, the PENN controller can follow the dynamic change of the processes. The training of network is simple and straightforward.
Keywords
MIMO systems; distillation; learning (artificial intelligence); level control; neural nets; neurocontrollers; nonlinear control systems; process control; MIMO distillation control; global policy; learning; local experience; nonlinear SISO water level control; online learning; policy-experience driven neural network; Chemical industry; Control systems; Delay effects; Industrial training; Knowledge engineering; Laboratories; MIMO; Neural networks; Stability; Telephony;
fLanguage
English
Publisher
ieee
Conference_Titel
Neural Networks, 1993. IJCNN '93-Nagoya. Proceedings of 1993 International Joint Conference on
Print_ISBN
0-7803-1421-2
Type
conf
DOI
10.1109/IJCNN.1993.714006
Filename
714006
Link To Document