Process Monitoring and Parameter Estimation via Unscented Kalman Filtering

摘要

One important aspect of process safety is detection of abnormal operating conditions. A common approach to this problem is that important states and parameters in a process are monitored and compared against their upper and lower bounds. However, some of these states and most of the parameters cannot be directly measured and instead have to be computed from plant data. This raises the question to what degree the results are affected by the procedure used for computing the values of unmeasured states and parameters. This paper presents a detailed comparison between several state estimation methodologies with a specific emphasis on unscented Kalman filtering as it is a relatively new technique.