SLUDGE DEWATERING PROCESS CONTROL USING PRINCIPAL COMPONENT ANALYSIS (PCA) AND PARTIAL LEAST SQUARE (PLS)

Authors

  • Grace Pebriyanti Universitas Papua Author
  • Renjie Zhu Tebodin Engineering & Construction Author
  • Adelhard Beni Rehiara Hiroshima University Author

Keywords:

Process control, Principal component analysis, Partial least squares, Sludge dewatering

Abstract

The process control in the sludge dewatering process is to minimalize the water volume in the sludge. However, management of this process control is difficult because of its multi-variables, nonlinearity and long delay. In this paper, a control approach based on the principal component analysis (PCA) is presented. A PCA model, which incorporates time lagged variables is used. The control objective is expressed in the score space of this PCA model. A controller is designed in the model predictive control framework, and it is used to control the equivalent score space representation of the process. The score predictive model for the model predictive control algorithm is built using a partial least squares (PLS). The process control system with PLS was simulated on Matlab and the graphs showed good accuracy and stability.

Downloads

Download data is not yet available.

Author Biographies

  • Grace Pebriyanti, Universitas Papua

    Engineering Department

  • Renjie Zhu, Tebodin Engineering & Construction

    Junior Engineering

  • Adelhard Beni Rehiara, Hiroshima University

    Department of Cybernetics, Graduate School of Engineering

References

Geladi, P., and Kowlaski, B. (1986). Partial least square regression: A tutorial. Analytica Chemica Acta. 35, 1-17.

Martens, H., and Naes, T. (1989). Multivariate Calibration, London: Wiley.

McIntosh, A. R., Bookstein, F. L., Haxby, J. V., and Grady, C. L. (1996). Spatial pattern analysis of functional brain images using partial least squares. Neuroimage, 3(3), 143-157.

Stigter, J. D. (2011). System Identification: An introduction. In MCSE programme HAN University. Netherlands.

Suykens, J. A., De Brabanter, J., Lukas, L., and Vandewalle, J. (2002). Weighted least squares support vector machines: robustness and sparse approximation. Neurocomputing, 48(1), 85-105.

Thyagarajan, T., Panda, R. C., Shanmugan, J., Rao, V. P. G., and Ponnavaikko, M. (1997). Development of ANN model for non-linear drying process. Drying technology, 15(10), 2527-2540.

Trelea, I. C., Trystram, G., and Courtois, F. (1997). Optimal constrained non-linear control of batch processes: application to corn drying. Journal of food engineering, 31(4), 403-421.

Turovskiy, I. S., and Mathai, P. K. (2006). Wastewater sludge processing. John wiley and sons.

Downloads

Published

2024-01-23

How to Cite

SLUDGE DEWATERING PROCESS CONTROL USING PRINCIPAL COMPONENT ANALYSIS (PCA) AND PARTIAL LEAST SQUARE (PLS). (2024). Indonesian Journal of Science and Technology, 1(1), 61-73. https://ejournal.kjpupi.id/index.php/ijost/article/view/226