The present work proposes a systematic nonlinear observer design framework for process monitoring. The objective is to accurately monitor key process variables associated with process safety or product quality, by designing a model-based nonlinear observer that directly utilizes the available information coming from continuous-time on-line process output measurements. The nonlinear observer possesses a state-dependent gain which is computed from the solution of a system of first-order linear partial differential equations (PDEs). Depending on whether the process operates in continuous or batch mode, a different mathematical treatment and solution scheme for the system of PDEs is needed. Within the proposed design framework, both full-order and reduced-order observers are studied. Finally, the performance of the proposed observer is evaluated in two chemical-engineering examples: (1) a catalytic batch reactor where the objective is to accurately estimate the catalyst activity and (2) an exothermic CSTR that exhibits steady-state multiplicity and the heat released by the reaction needs to be closely monitored.
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Kazantzis et al. (2000) studied this question.
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