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- W2033595707 abstract "Hybrid adaptive control strategy was developed and tested for the degradation of propylene glycol, a major component in de-icing waste, in an anaerobic fluidized bed bioreactor (AFBR). A linearized model with time-varying parameters was first employed to describe the dynamic behavior of the AFBR using a recursive off-line system identification method. A hybrid adaptive control strategy was then tested using a recursive off-line system identification routine followed by an on-line adaptive optimal control algorithm. The objective of the controller was to achieve the desired set point value of the propionate concentration (stand-alone control output variable) by manipulating the dilution rate (control input variable). To do so, the optimal control law was developed by minimizing a cost function with constraint equations. This novel idea was successfully applied to the underlying system for 200 h. The set point (700 mg HPrl(-1)) was achieved even in the case where the feed concentration suddenly increased by 50% (9000 mg HPrl(-1) to 13500 mg HPrl(-1))." @default.
- W2033595707 created "2016-06-24" @default.
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- W2033595707 date "2003-04-01" @default.
- W2033595707 modified "2023-10-17" @default.
- W2033595707 title "Hybrid adaptive optimal control of anaerobic fluidized bed bioreactor for the de-icing waste treatment" @default.
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- W2033595707 doi "https://doi.org/10.1016/s0168-1656(03)00018-x" @default.
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