Skip to main content

Real-Time Optimization of Industrial Processes

  • Living reference work entry
  • First Online:
Encyclopedia of Systems and Control

Abstract

RTO aims to optimize the operation of the process taking into account economic terms directly. There are several fundamental gears for smooth operating of an RTO solution. The RTO loop is an extension of feedback control system and consists of subsystems for (a) steady-state detection, (b) data reconciliation and measurement validation, (c) process model updating, and (d) model-based optimization followed by solution validation and implementation. There are several alternatives for each one of these subsystems. This contribution introduces some of the currently used approaches and gives some perspectives for future works in this area.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Institutional subscriptions

Similar content being viewed by others

Bibliography

  • Alkaya D, Vasamtharajan S, Biegler LT (2009) Successive quadratic programming: applications in the process industry. In: Floudas CA, Pardalos PM (eds) Encyclopedia of optimization. Springer, Berlin, pp 3853–3864

    Chapter  Google Scholar 

  • Bebar M (2005) Regelgütebewertung in kontinuierlichen verfahrenstechnischen Anlagen. Ruhr-Universität Bochum

    Google Scholar 

  • Biegler L (2010) Nonlinear programming: concepts, algorithms, and applications to chemical processes. MOS-SIAM series on optimization. Society for Industrial and Applied Mathematics: Mathematical Optimization Society, Philadelphia

    Book  Google Scholar 

  • Botelho VR, Trierweiler LF, Trierweiler JO (2012) A new approach for practical identifiability analysis applied to dynamic phenomenological models. Paper presented at the International symposium on advanced control of chemical processes – ADCHEM 2012, Singapura

    Google Scholar 

  • Boyd S, El Ghaoui L, Feron E, Balakrishnan V (1994) Linear matrix inequalities in system and control theory. Studies in applied and numerical mathematics. Society for Industrial and Applied Mathematics, Philadelphia

    Book  Google Scholar 

  • Cao S, Rhinehart RR (1995) An efficient method of on-line identification of steady state. Rev J Process Control 5:11

    Google Scholar 

  • Darby ML, Nikolaou M, Jones J, Nicholson D (2011) RTO: an overview and assessment of current practice. Rev J Process Control 21(6):874–884. doi:http://dx.doi.org/10.1016/j.jprocont.2011.03.009

    Google Scholar 

  • Engell S (2007) Feedback control for optimal process operation. Rev J Process Control 17(3):203–219. doi:http://dx.doi.org/10.1016/j.jprocont.2006.10.011

    Google Scholar 

  • François G, Srinivasan B, Bonvin D (2005) Use of measurements for enforcing the necessary conditions of optimality in the presence of constraints and uncertainty. Rev J Process Control 15(6):701–712. doi:http://dx.doi.org/10.1016/j.jprocont.2004.11.006

    Google Scholar 

  • Gao W, Engell S (2005) Iterative set-point optimization of batch chromatography. Rev Comput Chem Eng 29(6):1401–1409. doi:http://dx.doi.org/10.1016/j.compchemeng.2005.02.035

    Google Scholar 

  • Marchetti A, Chachuat B, Bonvin D (2009) Modifier-adaptation methodology for real-time optimization. Rev Ind Eng Chem Res 48(13):6022–6033. doi:10.1021/ie801352x

    Article  Google Scholar 

  • Mejía RIG, Duarte MB, Trierweiler JO (2010) Avaliação do desempenho e ajuste automático de métodos de identificação de estado estacionário. In: ABEQ (ed) COBEQ 2010 Congresso Brasileiro de Engenharia Química, 10, Foz do Iguaçú

    Google Scholar 

  • Miletic I, Marlin T (1996) Results analysis for real-time optimization (RTO): deciding when to change the plant operation. Rev Comput Chem Eng 20(Supplement 2):S1077-S1082. doi:http://dx.doi.org/10.1016/0098-1354(96)00187-1

    Google Scholar 

  • Narasimhan S, Jordache C (1999) The importance of data reconciliation and gross error detection-1. In: Data reconciliation and gross error detection. Gulf Professional, Burlington, pp 1–31

    Book  Google Scholar 

  • Sequeira SE, Graells M, Puigjaner L (2002) Real-time evolution for on-line optimization of continuous processes. Rev Ind Eng Chem Res 41(7):1815–1825. doi:10.1021/ie010464l

    Article  Google Scholar 

  • Skogestad S (2000) Plantwide control: the search for the self-optimizing control structure. Rev J Process Control 10(5):487–507. doi:http://dx.doi.org/10.1016/S0959-1524(00)00023-8

    Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Jorge Otávio Trierweiler .

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2014 Springer-Verlag London

About this entry

Cite this entry

Trierweiler, J.O. (2014). Real-Time Optimization of Industrial Processes. In: Baillieul, J., Samad, T. (eds) Encyclopedia of Systems and Control. Springer, London. https://doi.org/10.1007/978-1-4471-5102-9_243-1

Download citation

  • DOI: https://doi.org/10.1007/978-1-4471-5102-9_243-1

  • Received:

  • Accepted:

  • Published:

  • Publisher Name: Springer, London

  • Online ISBN: 978-1-4471-5102-9

  • eBook Packages: Springer Reference EngineeringReference Module Computer Science and Engineering

Publish with us

Policies and ethics