(444d) Inferential Control of A Continuous Digester: A Practical Perspective

Previous research by Hodges et al. [1, 2] had focused on the development of online near-infrared (NIR) spectroscopy to measure the compositions of three key liquid streams, i.e., white liquor, green liquor and black liquor, involved in the Kraft pulping process. Successful commercialization of this technology to the pulp and paper industry has made process control possible by providing key online, real-time measurements of the processes.

In this work, we focus on the process control of continuous digesters, which in the past had been hampered by insufficient and often delayed offline measurements. Implementing process control on digesters is both economically and environmentally desirable as successful process control can minimize variation in the Kappa number ? a direct indicator of pulp quality, and cut waste by reducing the usage of white liquor.

However, even with the availability of online process variable measurements, digester control is still very challenging because there are unmeasured disturbances, long time delays, nonlinear behavior and infrequent availability of the controlled variable (Kappa number) measurements [3]. Consequently, although advanced models and control strategies have been developed and validated using simulations by several researchers [3 ? 8], there are lacking of industrial implementations mainly due to the complexities involved in obtaining the models and carrying out the advanced control strategies. In this work, we revisit the control problem of continuous pulp digester, seeking to tackle this control problem in a more practical way.

In this work, we first implemented the simulation of a conventional single vessle digester based on the extended Purdue Model. Then different inferential control strategies are evaluated using the simulated digester. We compared two different inferential models which use the EA measurements to predict the kappa measurements. In addition, we also compared the performance of inferential controller with a cascade controller. Recommendations are given based on the controllers' performance, robustness and practical implementation considerations.

Key words: Digester control, inferential control, cascade control, feedforward-feedback control, nonlinearity, near-infrared spectroscopy

References:

1. Hodges, R.E., ?Applications of near infrared spectroscopy in the pulp and paper industry?, Ph.D. thesis, Auburn University Press, Auburn, AL, 1999

2. Hodges, R.E. and Krishnagopalan, G.A., ?Near-infrared spectroscopy for on-line analysis of white and green liquors?, TAPPI J., Vol. 82(9), 101, 1999

3. Wisnewski, P., Doyle III F.J. and Kayihan F., ?A fundamental continuous pulp digester model for simulation and control?, AIChE J., Vol. 43(12) p3175-3193, 1997

4. Wisnewski, P.A. and Doyle III, F.J. ?Control structure selection and model predictive control of the Weyerhaeuser digester problem?. J. Proc. Control, Vol. 8, 487-495, 1998

5. Wisnewski, P.A. and Doyle III, F.J., ?Model-based predictive control for a continuous pulp digester?, IEEE Trans. Control Syst. Tech. Vol. 9, 435?444, 2001

6. Lee, J.H. and Datta, A.K., ?Nonlinear inferential control of pulp digesters?, AIChE J. Vol. 40, 50?64, 1994

7. Amirthalingam, R. and Lee, J.H., ?Subspace identification based inferential control of a continuous pulp digester?, Comput. Chem. Eng. Vol. 21, 1143-1148, 1997

8. Amirthalingam, R. and Lee, J.H., ?Subspace identification based inferential control applied to a continuous pulp digester?, J. Proc. Control, Vol. 9(5), 397-406, 1999