State and parameter estimation for Tubular Microreactors using particle filter

Micro Chemical Processes (MCPs) are constructed of micrometer scale channels. The characteristics of MCPs are rapid mixing due to short diffusion distances and accurate temperature control due to large surface-volume ratio. Therefore, MCPs make it possible to realize the production of specialty chemicals, which cannot be handled in conventional processes. To realize stable long-term operation of MCPs, it is necessary to detect the catalyst deterioration and the blockage which are the critical problems in the operation of MCPs. For example, the catalyst deterioration and the blockage are detected through the concentration meters and the flow meters installed in microchannels respectively. However, the installation of such sensors sometimes disturbs the flow. In addition, the existing miniaturized sensors are too expensive. Therefore, it is necessary to develop a monitoring system of MCPs using the state and parameter estimation. In this work, a monitoring system based on physical models and wall temperature measurements for Tubular Microreactor (TMR) is developed. It is described that Particle Filter (PF) can detect the catalyst deterioration of TMR more rapidly and accurately than Extended Kalman Filter (EKF).