Real-time on-line adaptive control of processing systems is possible when the control algorithms include the ability to build multidimensional response surfaces the represent the processes being controlled. These response surfaces, or knowledgescapes, change in real time as processing conditions, process inputs and system parameters change. Continuous, on-line monitoring of these conditions, couple 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.
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