Title :
Knowledgescaping: on-line, adaptive optimizing control methods
Author :
Ynchausti, R.A. ; Hales, L.B. ; Gritton, K.S.
Author_Institution :
EIMCO Technol.
Abstract :
Real-time online adaptive control of processing systems is possible when the control algorithms include the ability to build multidimensional response surfaces that represent the processes being controlled. These response surfaces, or knowledgescapes, change in real time as processing conditions, process inputs and system parameters change. Continuous, online monitoring of these conditions, coupled with artificially intelligent tools, such as neural networks, to maintain current knowledgescape models of the process at any given time, and allow the control system to perform constrained optimization of any part, or all of the process system or enterprise. A knowledgescaping control system is described in this paper, and results for control of a milling operation are presented
Keywords :
adaptive control; computerised monitoring; intelligent control; neurocontrollers; online operation; optimal control; real-time systems; artificially intelligent tools; continuous online monitoring; knowledgescape models; multidimensional response surfaces; neural networks; online adaptive optimizing control methods; processing systems; real-time online adaptive control; Adaptive control; Artificial intelligence; Condition monitoring; Control systems; Multidimensional systems; Optimization methods; Process control; Programmable control; Real time systems; Response surface methodology;
Conference_Titel :
Dynamic Modeling Control Applications for Industry Workshop, 1997., IEEE Industry Applications Society
Conference_Location :
Vancouver, BC
DOI :
10.1109/DMCA.1997.603552