Comparison of advanced control strategies for improving the monitoring of activated sludge processes

Control Engineering Practice

Volumn 12, Issue 3, 2004, Pages 323-333

  Zarrad, W ^a   Harmand, J ^a   Devisscher, M ^b   Steyer, J P ^a  

^a LABORATOIRE DE BIOTECHNOLOGIE DE L ENVIRONNEMENT   (France)

^b Aquafin Belgium   (Belgium)

Author keywords

Biotechnology; Control; Disturbance rejection; Estimation

Indexed keywords

ACTIVATED SLUDGE PROCESS; BENCHMARKING; CONTROL EQUIPMENT; ESTIMATION; SENSORS; STABILITY;

BENCHMARKING MODELS; INDUSTRIAL CONTROL;

SEWAGE SLUDGE;

ACTIVATED SLUDGE; BIOTECHNOLOGY; MATHEMATICAL MODELING; MONITORING SYSTEM; PROCESS CONTROL; WASTEWATER TREATMENT;

EID: 1142305278     PISSN: 09670661     EISSN: None     Source Type: Journal    
DOI: 10.1016/S0967-0661(03)00169-2     Document Type: Article

References (13)

1. Anderson, B. D. O., & Moore, J. B. (1971). Linear optimal control. Englewood Cliffs, NJ: Prentice-Hall.
2. Andrews, J. F. (1974). Dynamic models and control strategies for wastewater treatment processes. Water Research, 8, 261-289.
3. Andrews, J. F. (1994). Dynamic control of wastewater treatment plants. Environmental Science Technology, 28, 434A-440A.
4. Farkas, J., Kralik, M., Derco, J., & Farkasova, P. (1991). Dynamic modelling of activated sludge process-IV. Multivariable statistical models. Chem. Papers, 45, 757-768.
5. Henze, M., Grady, C. P. L., Gujer, W., Marais, G. v. R., & Matsuo, T. (1986). Activated sludge model no. 1. IAWQ scientific and technical report no. 1, 33pp.
6. Johnson, C. D. (1976). Theory of disturbance accommodating control. In: C. Leondes (Ed.), Control and dynamic systems: Advances in theory and applications, Vol. 18 (pp. 387-489). London.
7. Ljung, L. (1995). System Identification Toolbox for use with MATLAB: user's guide.
8. 3-concentrations in alternating activated sludge processes. Journal of Process Control, 9, 87-100.
9. Pons, M. N., Spanjers, H., & Jeppsson, U. (1999). Towards a benchmark for evaluating control strategies in wastewater treatment plants by simulation. Computer Chemical Engineering (Suppl.), 23, S403-S406.
10. Skelton, R. E. (1989). Model error concepts in control design. International Journal of Control, 49, 1725-1753.
11. Takacs, I., Patry, G. G., & Nolasco, D. (1991). A dynamic model of the clarification-thickening process, Water Research, 25, 1263-1271.
12. The Mathworks Inc. (1998). SIMULINK 2.0: User's Guide.
13. Vanrolleghem, P. (1994). On-line modelling of activated sludge processes: development of an adaptive sensor. Thesis from the University of Gent, Belgium.