Dynamic Back-Propagation for Plant Identification and Control

• Main Authors: Nan-Ching Wang, 王南景
• Other Authors: Chi-Cheng Jou
• Format: Others
• Language: en_US
• Published: 1994
• Online Access: http://ndltd.ncl.edu.tw/handle/09703957867238072262

碩士 === 國立交通大學 === 控制工程系 === 82 === While much of the recent emphasis in the connectionist reseaarch has been on feedforward networks with static back- propagation, it is likely that the use of dynamic networks will be of particular importance in control-related applications. This thesis is focused on a learning methodology for recurrent networks with feedback connections and feedforward networks as subsystems in a dynamic system. Such a learning methodology is termed dynamic back-propagation, which is one of the most prominent learning methods for connectionist networks. A detailed study of dynamic back-propagation is presented to provide an insight of the principal ideas that contributed to the evolution of the concept and the details concerning its practical applications to identification and control.