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.
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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
Bebar M (2005) Regelgxxxomluxxxtebewertung in kontinuierlichen verfahrenstechnischen Anlagen. Ruhr-Universitxxxomlaxxxt Bochum
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
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
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
Cao S, Rhinehart RR (1995) An efficient method of on-line identification of steady state. Rev J Process Control 5:11
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://doi.org/10.1016/j.jprocont.2011.03.009
Engell S (2007) Feedback control for optimal process operation. Rev J Process Control 17(3):203–219. doi:http://doi.org/10.1016/j.jprocont.2006.10.011
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://doi.org/10.1016/j.jprocont.2004.11.006
Gao W, Engell S (2005) Iterative set-point optimization of batch chromatography. Rev Comput Chem Eng 29(6):1401–1409. doi:http://doi.org/10.1016/j.compchemeng.2005.02.035
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
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
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://doi.org/10.1016/0098-1354(96)00187-1
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
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
Skogestad S (2000) Plantwide control: the search for the self-optimizing control structure. Rev J Process Control 10(5):487–507. doi:http://doi.org/10.1016/S0959-1524(00)00023-8
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Trierweiler, J.O. (2021). Real-Time Optimization of Industrial Processes. In: Baillieul, J., Samad, T. (eds) Encyclopedia of Systems and Control. Springer, Cham. https://doi.org/10.1007/978-3-030-44184-5_243
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DOI: https://doi.org/10.1007/978-3-030-44184-5_243
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