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The New Approach for Dynamic Optimization with Variability Constraints

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Recent Advances in Computational Optimization

Part of the book series: Studies in Computational Intelligence ((SCI,volume 795))

Abstract

In this work a new optimization approach for processes modeled by differential-algebraic equations with variability constraints was presented. The designed procedure was based on the modified direct shooting method, which can transform the dynamic optimization problem into a large-scale nonlinear optimization task (NLP). The first-order KKT optimality conditions with complementarity constraints were obtained. Finally, to solve the optimality conditions with the complementarity constraints, the solution procedure combining SQP algorithm with the filter approach as a globalization procedure was designed. The efficiency of the presented methodology was tested on a production process in chemical engineering.

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Acknowledgements

One of the co-authors, Paweł Dra̧g, received financial support in the framework of “Młoda Kadra”- “Young Staff” 0402/0109/17 at Wrocław University of Science and Technology.

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Authors and Affiliations

  1. Department of Control Systems and Mechatronics, Wrocław University of Science and Technology, Janiszewskiego 11/17, 50-370, Wrocław, Poland

    Paweł Dra̧g & Krystyn Styczeń

Authors
  1. Paweł Dra̧g
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  2. Krystyn Styczeń
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Corresponding author

Correspondence to Paweł Dra̧g .

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Editors and Affiliations

  1. Department of Parallel Algorithms, Institute of Information and Communication Technologies, Bulgarian Academy of Sciences, Sofia, Bulgaria

    Stefka Fidanova

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Dra̧g, P., Styczeń, K. (2019). The New Approach for Dynamic Optimization with Variability Constraints. In: Fidanova, S. (eds) Recent Advances in Computational Optimization. Studies in Computational Intelligence, vol 795. Springer, Cham. https://doi.org/10.1007/978-3-319-99648-6_3

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