Abstract
In a changing operational environment, a major challenge that still exits is the assured state and parameter estimation of dynamic processes. The values or expressions of important parameters can be difficult to determine and initial errors may be present in some parameters as a result of changes in the initial operating conditions. Furthermore as a result of variations in the environmental and operational conditions or the dynamic characteristics of the process, parameters may be time-varying. In this paper, an on-line Bayesian parameter estimator is developed and evaluated on a simulation of a batch methyl methacrylate process.
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