A cascade control strategy is proposed to the benchmark simulation model 1 (BSM1) to enhance the treatment performance of nitrogen removal in a biological wastewater treatment plant. The proposed control approach consists of two control loops, a primary outer loop and a secondary inner loop. The method has two controllers of which the primary loop has a model predictive control (MPC) controller and the secondary loop has a proportional-integralderivative (PID) controller, which is a cascade MPC-PID controller. The primary MPC controller is to control the nitrate concentration in the effluent, and the secondary PID controller is to control the nitrate concentration in the final anoxic compartment. The proposed method controls the nitrate concentrations in the effluent as well as in the final anoxic reactor simultaneously to strictly satisfy the quality of the effluent as well as to remove the effects of disturbances more_x000D_ quickly by manipulating the external carbon dosage rate. Because the control performance assessment (CPA) technique has the features of determining the capability of the current controller and locating the best achievable performance, the other novelty of this paper is to suggest a relative closed-loop potential index (RCPI) which updates the CPA technology_x000D_ into a closed-loop cascade controller. The proposed method is compared with a cascade PID-PID control strategy and the original PID controller in BSM1 and an improved performance of the suggested cascade MPC-PID controller is obtained by using the CPA approach.

Control Performance Assessment Cascade Control Model Predictive Control Wastewater Treatment Process BSM1 Benchmark

Isaacs SH, Henze M, Søeberg H, Kummel M, Water Res., 28, 511 (1994)
Isaacs SH, Henze M, Water Res., 29, 77 (1995)
Alex J, Beteau JF, Copp JB, Hellinga C, Jeppsson U, Marsili Libelli S, Pons M, Spanjers H, Vanhooren H, European Control Conference 99, Germany: Karlsruhe, Karlsruhe (1999)
Copp J, The cost simulation benchmark: Description and simulator manual, Office for official publications of the European Community (2002)
Alex J, Benedetti L, Copp J, Gernaey K, Jeppsson U, Nopens I, Pons M, Rieger L, Rosen C and Steyer J, Report by the IWA Task Taskgroup on Benchmarking of Control Strategies for WWTPs (2008)
Lindberg C, Carlsson B, Water Sci. Technol., 34, 173 (1996)
Yuan Z, Bogaert H, Vanrolleghem P, Thoeye C, Vansteenkiste G, Verstraete W, J. Environ. Eng., 123, 1080 (1997)
Barros P, Carlsson B, Water Sci. Technol., 37, 95 (1998)
Singman J, Uppsala University, Uppsala (1999)
Cho J, Sung S, Lee I, Water Sci. Technol., 45, 53 (2002)
Jelali M, Control Eng. Pract., 14, 441 (2006)
Yoo CK, Kim DS, Cho JH, Choi SW, Lee IB, Korean J. Chem. Eng., 18(4), 408 (2001)
Henze M, Grady CPL Jr , Gujer W, Marais GVR, Matsuo T, IAWPRC Scientific and Technicat Report No. 1, Bristol (1987)
Henze M, Grady CPL Jr, Gujer W, Marais GVR, Matsuo T, Water Res., 21, 505 (1987)
Takacs I, Patry G, Nolasco D, Water Res., 25, 1263 (1991)
Vanhooren H and Nguyen K, University of Ghent and University of Ottawa, Belgium (1996)
Franks RG, Worley CW, Ind. Eng. Chem., 48, 1074 (1956)
Lee YH, Park SW, Lee JH, Ind. Eng. Chem. Res., 39(1), 92 (2000)
Shen WH, Chen XQ, Corriou JP, Comput. Chem. Eng., 32(12), 2849 (2008)
Shen WH, Chen XQ, Pons MN, Corriou JP, Chem. Eng. J., 155(1-2), 161 (2009)
Harris TJ, Can. J. Chem. Eng., 67, 856 (1989)
Qin SJ, Comput. Chem. Eng., 23(2), 173 (1998)
Huang B and Shah S, Performance assessment of control loops: Theory and applications, Springer (1999)
Qin SJ, Yu J, J. Process Control, 17(3), 221 (2007)
Huang B and Kadali R, Dynamic modeling, predictive control and performance monitoring: A data-driven subspace approach, Springer Verlag (2008)
Horch A, Dumont G, Int. J. Adapt. Control., 17, 523 (2003)
Yuan QL, Lennox B, McEwan M, J. Process Control, 19(5), 751 (2009)
Huang B, Ding SX, Thornhill N, J. Process Control, 16(5), 457 (2006)
Astrom KJ, Hagglund T, Automatica., 20, 645 (1984)
Sung S, Lee J, Lee I, Process identification and pid control, Wiley-Blackwell (2009)
Zhu Y, Multivariable system identification for process control, Elsevier Science (2001)
Ljung L, System identification: Theory for the user, Prentice-Hall Englewood Cliffs, NJ (1999)
Maciejowski JM, Predictive control with constraints, Prentice-Hall (2002)
Seborg D, Edgar T and Mellichamp D, Process dynamics and control, Wiley (2004)