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- W2899642791 abstract "Abstract This chapter describes the application of two different automatic controllers for the ozonation of contaminated water. The first approach uses the new method to design a local optimal controller for ozonation. The online solution of the adaptive gains adjusting a linear control form yields the calculus of the suboptimal controller. A special performance index, meant to solve the transient evolution of such systems, is proposed. The class of systems considered in this study is highly uncertain: some components of chemical reactions are not measurable online, 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 a particular example of ozonation) is evaluated in detail using the control design proposed here. The second controller uses a trajectory tracking adaptive controller based on DNN to control the ozonation system. This approach uses a nonlinear transformation of the ozonation model to obtain a chain-of-integrators equivalent form. This controller was applied on the simple ozonation model with only one contaminant. The numerical and experimental validation of the tracking controller justifies both designs." @default.
- W2899642791 created "2018-11-16" @default.
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- W2899642791 date "2019-01-01" @default.
- W2899642791 modified "2023-10-18" @default.
- W2899642791 title "Automatic control of ozonation systems in liquid phase" @default.
- W2899642791 doi "https://doi.org/10.1016/b978-0-12-812847-3.00018-4" @default.
- W2899642791 hasPublicationYear "2019" @default.
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