DocumentCode
1688104
Title
An improved associative memory learning control system for industrial processes with unknown dynamics
Author
Xu, Ning-Shou ; Wu, Zhang-Lei ; Qu, Gui-Hong ; Chen, Li-Ping ; Wang, Guang-Shen ; Zhang, Hong
Author_Institution
Dept. of Automatic Control, Beijing Polytech. Univ., China
fYear
1992
Firstpage
198
Abstract
This paper proposes an improved version of the associative memory learning control system (AMLCS) for industrial processes with almost completely unknown but slowly time-varying dynamics. Numerical simulations have shown the feasibility and effectiveness of the new AMLCS proposed
Keywords
control system synthesis; learning systems; neural nets; process computer control; time-varying systems; associative memory learning control system; control system synthesis; industrial processes; neural nets; process computer control; simulations; time-varying dynamics; unknown dynamics; Associative memory; Automatic control; Brain modeling; Control systems; Electrical equipment industry; Industrial control; Neural networks; Predictive models; Process control; Size control;
fLanguage
English
Publisher
ieee
Conference_Titel
Industrial Electronics, 1992., Proceedings of the IEEE International Symposium on
Conference_Location
Xian
Print_ISBN
0-7803-0042-4
Type
conf
DOI
10.1109/ISIE.1992.279588
Filename
279588
Link To Document