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- W4210572306 abstract "Optimal state estimation has a significant role in the monitoring and control of distributed dynamic systems. This chapter presents a sensor selection and state estimation strategy for distributed dynamic systems, in which an empirical observability Grammian-based methodology is used to configure the sensor locations and an unscented Kalman filter is employed for state estimation. The performance of the measurement selection methodology and state estimation scheme is evaluated by applying it to a catalytic tubular reactor, in which partial oxidation of benzene takes place to produce maleic anhydride. The Grammian configured temperature sensors are employed for instantaneous estimation of reactant and product concentration profiles in the tubular reactor. The results demonstrate the usefulness of the sensor selection methodology and state estimation scheme for inferential estimation of states in the catalytic tubular reactor." @default.
- W4210572306 created "2022-02-08" @default.
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- W4210572306 date "2022-01-01" @default.
- W4210572306 modified "2023-10-16" @default.
- W4210572306 title "Application of mechanistic model-based nonlinear filtering and observation techniques for optimal state estimation of a catalytic tubular reactor with optimal sensor configuration" @default.
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- W4210572306 doi "https://doi.org/10.1016/b978-0-323-85878-6.00019-1" @default.
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