Hybrid adaptive optimal control of anaerobic fluidized bed bioreactor for the de-icing waste treatment.
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)).
Seok
Jonghyuk
J
Water Environment and Remediation Center, KIST, P.O. Box 131, Cheongryang, 130-650, Seoul, South Korea. seokj@alum.rpi.edu
D000465:Algorithms; D001421:Bacteria, Anaerobic / Q000254:growth & development* / Q000378:metabolism*; D001673:Biodegradation, Environmental; D019149:Bioreactors / Q000382:microbiology*; D018929:Cell Culture Techniques / Q000379:methods*; D003198:Computer Simulation; D005246:Feedback; D007220:Industrial Waste / Q000517:prevention & control; D008954:Models, Biological; D019946:Propylene Glycol / Q000378:metabolism*; D012997:Solvents / Q000378:metabolism; D014865:Waste Disposal, Fluid / Q000379:methods*; D014874:Water Pollutants, Chemical / Q000378:metabolism
D007220:Industrial Waste; D012997:Solvents; D014874:Water Pollutants, Chemical; D019946:Propylene Glycol