Intelligent Monitoring of Advanced Control and Optimization

An optimal performance of process controllers and control loops is essential for process economy as well as process quality. The increased cost of energy and raw material as well as customer demand for quality requirements are forcing the control engineers to develop and provide solutions, which can operate in ever changing process conditions cost efficiently without compromising safety. Based on statistics, only a fraction of used control loops are performing at optimum level. In a multivariate process there can be dozens control loops to be monitored, which makes manual inspection difficult. Therefore, a system that automatically evaluates the process state and helps predicting future outcomes using real time optimization and offline data analysis is in order. A control loop performance monitoring system is often used as a support for control optimization. It can also be used for inspection of process actuator condition. A process performance monitoring tools usually makes use of statistical and mathematical methods with a visual user interface to provide adequate amount of data. In this thesis, two process performance monitoring tools for advanced control and opti-mization were implemented. The tools are used to monitor selected control methods, providing essential information about their status. The usefulness of a process perfor-mance monitoring system is demonstrated at a site using real process data. The tools were included into an existing process monitoring system that was already in place at a process site