Abstract
A new method to design local optimal controller for uncertain system governed by continuous flow transformations (CFT) is presented. The on-line solution of the adaptive gains adjusting a linear control form yields the calculus of the sub-optimal controller. A special performance index, oriented to solve the transient evolution of CFT systems, is proposed. The class of systems considered in this study is highly uncertain: some components of chemical reactions are no measurable on line and then, they cannot be used in the controller realization. The recovering of this information was executed by a differential neural network (DNN) structure. The ozonation process of a single contaminant (as the particular example of CFT) is evaluated in detail using the control design proposed here.
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Poznyak, T., Chairez, I., Poznyak, A. (2018). Residence Time Regulation in Chemical Processes: Local Optimal Control Realization by Differential Neural Networks. In: Huang, T., Lv, J., Sun, C., Tuzikov, A. (eds) Advances in Neural Networks – ISNN 2018. ISNN 2018. Lecture Notes in Computer Science(), vol 10878. Springer, Cham. https://doi.org/10.1007/978-3-319-92537-0_85
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DOI: https://doi.org/10.1007/978-3-319-92537-0_85
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