Abstract
In this chapter, chemical industrial processes are considered, and Linear Algebra-Based Control Design (LAB CD) is the approach used to design the controller. First, the case of dealing with a nonlinear first principles–based model of the process is considered. Then, an experimental linearized model around an operating point is considered, and, again, the LAB CD methodology is applied to design the control. The simple model based on a first-order plus time delay (FOPTD) transfer function is used, and the controlled plant behavior is shown to be appropriate for small changes in the reference. A gain-scheduling adaptation scheme is suggested for larger reference changes. Thence, a design applicable to a large variety of processes is obtained. In order to better illustrate the procedure, the control design for a typical continuous stirred tank reactor (CSTR) is developed.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
References
Bonvin, D., & Francois, G. (2017). Control and optimization of batch chemical processes. Coulson and Richardson's Chemical Engineering. Volume 3 (Chemical & Biochemical Reactors, and Process Control), 4th Edition, by J.F. Richardson and D.G. Peacock (Eds).
Camacho, O. A., & Smith, C. (2000). Sliding mode control: An approach to regulate nonlinear chemical processes. ISA Transactions, 39, 205–218.
Fern´ndez, M. C., Pantano, M. N., Rossomando, F., Ortiz, O. A., Scaglia, G., & Scaglia, J. E. (2019). State estimation and trajectory tracking control for a nonlinear and multivariable bioethanol production system. Brazilian Journal of Chemical Engineering, 36(1), 421–437. https://doi.org/10.1590/0104-6632.20190361s20170379.
Coughanowr, C., Ansara, I., Luoma, R., Hamalainen, M., & Lukas, H. L. (1991). Assessment of the Cu-Mg system. Zeitschrift für Metallkunde, 82(7), 574–581.
Liu, T., Wang, Q. G., & Huang, H. P. (2013). A tutorial review on process identification from step or relay feedback test. Journal of Process Control, 23(10), 1597–1623.
Luyben, W. L. (1990). Process modeling, simulation and control for chem. engineers. Singapore: McGraw-Hill.
Pantano, M. N., Serrano, M. E., Fernandez, M. C., Rossomando, F. G., Ortiz, O. A., & Scaglia, G. J. E. (2017). Multivariable control for tracking optimal profiles in a nonlinear fed-batch bioprocess integrated with state estimation. Industrial and Engineering Chemistry Research, 56, 6043–6056.
Ray, W.H. (1981). New approaches to the dynamics of nonlinear systems with implications for process and control system design. United States: N. p., 1981. Web.
Rómoli, S., Serrano, M. E., Ortiz, O. A., Vega, J. R., & Scaglia, G. J. E. (2015). Tracking control of concentration profiles in a fed-batch bioreactor using a linear algebra methodology. ISA Transactions, 57, 162–171. https://doi.org/10.1016/j.isatra.2015.01.002.
Sardella, M. F., Serrano, M. E., Camacho, O., & Scaglia, G. (2019). Design and application of a linear algebra based controller from a reduced-order model for regulation and tracking of chemical processes under uncertainties. Industrial & Engineering Chemistry Research Publisher: American Chemical Society, 1, 2019. https://doi.org/10.1021/acs.iecr.9b01257.
Seborg, D. E., Edgar, T. F., Mellichamp, D. A., & Doyle, F. J., III. (2011). Process dynamics and control (3rd ed.). Hoboken, NJ: Wiley.
Smith, C. A., & Corripio, A. B. (1997). Principles and practice of automatic process control. Hoboken, NJ: Wiley.
Stephanopoulos, G., & Vallino, J. J. (1991). Network rigidity and metabolic engineering in metabolite overproduction. Science, 252(5013), 1675–1681.
Tempo, R., & Ishii, H. (2007). Monte Carlo and Las Vegas randomized algorithms for systems and control. European Journal of Control, 13, 189–203.
Author information
Authors and Affiliations
Rights and permissions
Copyright information
© 2020 Springer Nature Switzerland AG
About this chapter
Cite this chapter
Scaglia, G., Serrano, M.E., Albertos, P. (2020). Application to Industrial Processes. In: Linear Algebra Based Controllers. Springer, Cham. https://doi.org/10.1007/978-3-030-42818-1_6
Download citation
DOI: https://doi.org/10.1007/978-3-030-42818-1_6
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-030-42817-4
Online ISBN: 978-3-030-42818-1
eBook Packages: Intelligent Technologies and RoboticsIntelligent Technologies and Robotics (R0)