(317f) Optimal Sensor Location and State Estimation for Microreactors | AIChE

(317f) Optimal Sensor Location and State Estimation for Microreactors


Tonomura, O. - Presenter, Kyoto university
Nagahara, S. - Presenter, Kyoto University
Kano, M. - Presenter, Kyoto University

Worldwide research has clearly demonstrated the application potential of micro chemical process technology, which brings many advantages of higher product yield and selectivity, improved safety, and synthesis of new functional materials. In order to use micro chemical process technology in production processes, a number of technical and economical requirements have to be met. One of the dominant requirements is to ensure long-term stable operation of micro chemical processes by using suitable process monitoring and control techniques. Monitoring and control of micro chemical processes is based on the measurements available from installed measurement systems. As the number of sensors becomes large, the information that can be obtained from the process will be increased. However, the miniaturized sensors are expensive in terms of the initial as well as the maintenance costs, and the installation of such sensors often disturbs the flow in microchannels and generates dead volume. Therefore, it is important to develop a state estimation system that makes it possible to reconstruct unmeasured variables from a few on-line measured variables. To achieve the best performance of the state estimation system, the sensors also have to be placed at the optimal locations. In this research, a process monitoring system for a tubular microreactor in which a first-order exothermic catalytic reaction takes place is developed, and the optimal location of a single temperature sensor is derived to achieve the most accurate estimation of the product concentration profile. The results of the case studies indicate that the heat capacity of walls should be modeled, which is often ignored in conventional reactors, and that the derived optimal sensor location is robust against the variation of operating conditions. This research demonstrates promising developments for the monitoring system of micro chemical processes.


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