Multivariable control of nutrient-removing activated sludge systems

The aim of this paper is to evaluate several multivariable model-based control algorithms for controlling nitrogen removal in activated sludge processes. We contend that the control of nutrient removal in activated sludge systems is a multivariable control problem, rather than a multiloop problem. The work is a simulation study of a predenitrification activated sludge plant. Several model-based controllers are evaluated and compared against a base-case and multiloop controller. We introduce a quantitative measure to aid in controller evaluation. Model based control algorithms are shown to be able to provide tight control of N removal, thereby offering significant benefits in terms of deferred capital expenditure. This is in return for increased operating costs.

[1]  Bengt Carlsson,et al.  Iterative design of a nitrate controller using an external carbon source in an activated sludge process , 1998 .

[2]  Bengt Carlsson,et al.  Nonlinear and set-point control of the dissolved oxygen concentration in an activated sludge process , 1996 .

[3]  Joseph P. Shunta,et al.  Achieving World Class Manufacturing Through Process Control , 1994 .

[4]  Bengt Carlsson,et al.  Adaptive control of external carbon flow rate in an activated sludge process , 1996 .

[5]  R. B. Newell,et al.  A systematic approach for reducing complex biological wastewater treatment models , 1997 .

[6]  South Carolina,et al.  Control strategies for the activated sludge process , 1980 .

[7]  H. Stehfest,et al.  Optimal periodic control of a steep‐feed activated sludge plant , 1985 .

[8]  Evanghelos Zafiriou,et al.  Robust process control , 1987 .

[9]  C. De Prada,et al.  Identification and constrained multivariable predictive control of chemical reactors , 1995, Proceedings of International Conference on Control Applications.

[10]  T. M. Keinath.  Operational dynamics and control of secondary clarifiers , 1985 .

[11]  Maciejowsk.  Multivariable Feedback Design , 1989 .

[12]  Gustaf Olsson,et al.  Simultaneous DO Control and Respiration Estimation , 1989 .

[13]  M. Morari,et al.  Internal model control. VI: Extension to nonlinear systems , 1986 .

[14]  G. R. Sullivan,et al.  Generic model control (GMC) , 1988 .

[15]  C. J. King,et al.  Spray drying food liquids and the retention of volatiles. , 1990 .

[16]  W. Gujer,et al.  A general model for single-sludge wastewater treatment systems , 1987 .

[17]  Thomas F. Edgar,et al.  MODEL-BASED CONTROL: A SURVEY , 1992 .

[18]  Gustaf Olsson,et al.  Establishing Cause-Effect Relationships in Activated Sludge Plants - what Can Be Controlled , 1994 .

[19]  I-Lung Chien,et al.  Consider IMC Tuning to Improve Controller Performance , 1990 .

[20]  Paul Lant,et al.  Benchmarking for process control: “Should i invest in improved process control?” , 1998 .

[21]  M. Kümmel,et al.  Nonlinear optimal control of an alternating activated sludge process in a pilot plant , 1994 .

[22]  Moses O. Tadé,et al.  Nonlinear control of a simulated industrial evaporation process , 1995 .

[23]  Graham C. Goodwin,et al.  Control System Design , 2000 .

[24]  B. Carlsson.  On-Line Estimation of the Respiration Rate in an Activated Sludge Process , 1993 .

[25]  David W. Clarke,et al.  Generalized predictive control - Part I. The basic algorithm , 1987, Autom..

[26]  C. R. Cutler,et al.  Dynamic matrix control¿A computer control algorithm , 1979 .

[27]  Gustaf Olsson,et al.  Integration of WWT Plant Design and Operation - a Systematic Approach Using Cost Functions , 1996 .

[28]  Peter A. Vanrolleghem,et al.  Improved design and control of industrial and municipal nutrient removal plants using dynamic models , 1997 .

[29]  M. Morari,et al.  Internal Model Control: extension to nonlinear system , 1986 .

[30]  Manfred Morari,et al.  Model predictive control: Theory and practice - A survey , 1989, Autom..