Skip to main content

Direct Shooting Method for Optimal Control of the Highly Nonlinear Differential-Algebraic Systems

  • Chapter
  • First Online:
Recent Advances in Computational Optimization

Part of the book series: Studies in Computational Intelligence ((SCI,volume 610))

  • 966 Accesses

Abstract

In the paper the optimal control of highly nonlinear differential-algebraic systems (DAEs) is discussed. The direct shooting method is seen as an efficient tool for control of the complex real-life technological processes, where dynamics and conservation laws are presented. To stabilize the optimization algorithm, the multiple shooting method was proposed. The multiple shooting approach introduces new decision variables and constraints to the problem, but it can preserve the stability of the process, the continuity of the differential state trajectories and enables parallel computation of the mathematical model. The conditions for the frequency of shots, to establish the well-conditioned optimization problem, are considered. The proposed method was tested on the mathematical model of the fed-batch fermentor for penicillin production process, which is a highly nonlinear multistage differential-algebraic system. The numerical simulations were executed in MATLAB environment using Wroclaw Center for Networking and Supercomputing.

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

Access this chapter

eBook
USD 16.99
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Hardcover Book
USD 109.99
Price excludes VAT (USA)
  • Durable hardcover edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

References

  1. E. Balsa-Canto, V.S. Vassiliadis, J.R. Banga, Dynamic optimization of single and multi-stage systems using a hybrid stochastic-deterministic method. Ind. Eng. Chem. Res 44, 1514–1523 (2005)

    Article  Google Scholar 

  2. J.R. Banga, E. Balsa-Canto, C.G. Moles, A.A. Alonso, Dynamic optimization of bioprocesses: efficient and robust numerical strategies. J. Biotechnol. 117, 407–419 (2005)

    Article  Google Scholar 

  3. J.T. Betts, Practical Methods for Optimal Control and Estimation Using Nonlinear Programming, 2nd edn. (SIAM, Philadelphia, 2010)

    Book  MATH  Google Scholar 

  4. L.T. Biegler, Nonlinear Programming, Concepts, Algorithms and Applications to Chemical Processes (SIAM, Philadelphia, 2010)

    Google Scholar 

  5. L.T. Biegler, S. Campbell, V. Mehrmann, DAEs, Control, and Optimization, in Control and Optimization with Differential-Algebraic Constraints, ed. by L.T. Biegler, S. Campbell, V. Mehrmann (SIAM, Philadelphia, 2012)

    Chapter  Google Scholar 

  6. L.T. Biegler, I.E. Grossmann, Retrospective on optimization. Comput. Chem. Eng. 28, 1169–1192 (2004)

    Article  Google Scholar 

  7. K.E. Brenan, S.L. Campbell, L.R. Petzold, Numerical Solution of Initial-Value Problems in Differential-Algebraic Equations (SIAM, Philadelphia, 1996)

    MATH  Google Scholar 

  8. M. Cannon, Efficient nonlinear model predictive control algorithms. Annu. Rev. Control 28, 229–237 (2004)

    Article  Google Scholar 

  9. M. Caracotsios, W.E. Stewart, Sensitivity analysis of initial value problems with mixed ODEs and algebraic equations. Comput. Chem. Eng. 9, 359–365 (1985)

    Article  Google Scholar 

  10. E.F. Carrasco, J.R. Banga, Dynamic optimization of batch reactors using adaptive stochastic algorithms. Ind. Eng. Chem. Res. 36, 2252–2261 (1997)

    Article  Google Scholar 

  11. M. Diehl, H.G. Bock, J.P. Schlöder, R. Findeisen, Z. Nagy, F. Allgöwer, Real-time optimization and nonlinear model predictive control of processes governed by differential-algebraic equations. J. Process Control 12, 577–585 (2002)

    Article  Google Scholar 

  12. P. Dra̧g, K. Styczeń, A two-step approach for optimal control of kinetic batch reactor with electroneutrality condition. Przegla̧d Elektrotechniczny 6(88), 176–180 (2012)

    Google Scholar 

  13. A. Flores-Tlacuahuac, L.T. Biegler, E. Saldivar-Guerra, Dynamic optimization of hips open-loop unstable polymerization reactors. Ind. Eng. Chem. Res. 44, 2659–2674 (2005)

    Article  Google Scholar 

  14. A. Flores-Tlacuahuac, S.T. Moreno, L.T. Biegler, Global optimization of highly nonlinear dynamic systems. Ind. Eng. Chem. Res. 47, 2643–2655 (2008)

    Article  Google Scholar 

  15. I.E. Grossmann, L.T. Biegler, Part II. Future perspective on optimization. Comput. Chem. Eng. 28, 1193–1218 (2004)

    Article  Google Scholar 

  16. A. Hartwich, K. Stockmann, C. Terboven, S. Feuerriegel, W. Marquardt, Parallel sensitivity analysis for efficient large-scale dynamic optimization. Optim. Eng. 12, 489–508 (2011)

    Article  MathSciNet  MATH  Google Scholar 

  17. D.B. Leineweber, I. Bauer, H.G. Bock, J.P. Schlöder, An efficient multiple shooting based reduced SQP strategy for large scale dynamic process optimization. Part 1: Theoretical aspects. Comput. Chem. Eng. 27, 157–166 (2003)

    Article  Google Scholar 

  18. J. Nocedal, S.J. Wright, Numerical Optimization, 2nd edn. (Springer, New York, 2006)

    MATH  Google Scholar 

  19. K. Styczeń, P. Dra̧g. A modified multipoint shooting feasible-SQP method for optimal control of DAE systems. Proceedings of the Federated Conference on Computer Science and Information Systems, Szczecin, Poland, pp. 477–484, 18–21 September 2011

    Google Scholar 

  20. V.S. Vassiliadis, R.W.H. Sargent, C.C. Pantelides, Solution of a class of multistage dynamic optimization problems. 1. Problems without path constraints. Ind. Eng. Chem. Res. 33, 2111–2122 (1994)

    Article  Google Scholar 

  21. V.S. Vassiliadis, R.W.H. Sargent, C.C. Pantelides, Solution of a Class of Multistage Dynamic Optimization Problems. 2. Problems with Path Constraints. Ind. Eng. Chem. Res. 33, 2123–2122 (1994)

    Article  Google Scholar 

Download references

Acknowledgments

The project was supported by the grant of National Science Centre Poland DEC-2012/07/B/ST7/01216.

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Paweł Dra̧g .

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2016 Springer International Publishing Switzerland

About this chapter

Cite this chapter

Dra̧g, P., Styczeń, K. (2016). Direct Shooting Method for Optimal Control of the Highly Nonlinear Differential-Algebraic Systems. In: Fidanova, S. (eds) Recent Advances in Computational Optimization. Studies in Computational Intelligence, vol 610. Springer, Cham. https://doi.org/10.1007/978-3-319-21133-6_5

Download citation

  • DOI: https://doi.org/10.1007/978-3-319-21133-6_5

  • Published:

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-21132-9

  • Online ISBN: 978-3-319-21133-6

  • eBook Packages: EngineeringEngineering (R0)

Publish with us

Policies and ethics