Title :
Learning in semantic control
Author :
Kokar, Mieczyslaw M. ; Keshav, Satyadev N. ; Gopalraman, Subbiah ; Lirov, Yuval
Author_Institution :
Dept. of Ind. Eng. & Inf. Syst., Northeastern Univ., Boston, MA, USA
Abstract :
The authors deal with a control problem when the control objective is to keep the system within some qualitative region called safe. It is assumed that the system is evolving over time, i.e. it is changing its qualitative and quantitative characteristics. This is reflected in the qualitative change of the model of the system which, as a result, must be permanently updated. The goal is to develop a theoretical approach which would provide a methodology for automatic construction of such controllers which are able to solve the above control problem. An approach to the solution of this problem is presented that is based on a combination of control theory and artificial intelligence
Keywords :
learning systems; artificial intelligence; control theory; learning systems; semantic control; Artificial intelligence; Automatic control; Control system synthesis; Control systems; Control theory; Expert systems; Industrial engineering; Machine learning; Machine learning algorithms; Power system modeling;
Conference_Titel :
Decision and Control, 1988., Proceedings of the 27th IEEE Conference on
Conference_Location :
Austin, TX
DOI :
10.1109/CDC.1988.194640
