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International Conference on Automation

ICA 2016: Challenges in Automation, Robotics and Measurement Techniques pp 189–205Cite as

Shooting Methods to Solve Optimal Control Problems with State and Mixed Control-State Constraints

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Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 440))

Abstract

The paper presents two important approaches to solve numerically general optimal control problems with state and mixed control-state constraints. They may be attractive in the case, when the simple time discretization of the state equations and expressing the optimal control problem as a nonlinear mathematical programming problem is not sufficient. At the beginning an extension of the optimal control theory to problems with constraints on current state and on current state and control simultaneously is presented. Then, two approaches to solve numerically the emerging boundary value problems: indirect and direct shooting method are described and applied to an example problem.

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Notes

  1. 1.

    In our convention a gradient of a scalar function is a column vector.

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Author information

Authors and Affiliations

  1. Institute of Control and Computation Engineering, Warsaw University of Technology, Warsaw, Poland

    Andrzej Karbowski

  2. NASK, Research and Academic Computer Network, Warsaw, Poland

    Andrzej Karbowski

Authors
  1. Andrzej Karbowski
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Correspondence to Andrzej Karbowski .

Editor information

Editors and Affiliations

  1. Automation and Measurements PIAP, Industrial Research Institute for, Warsaw, Poland

    Roman Szewczyk

  2. Automation and Measurements PIAP, Industrial Research Institute for, Warsaw, Poland

    Cezary Zieliński

  3. Automation and Measurements PIAP, Industrial Research Institute for, Warsaw, Poland

    Małgorzata Kaliczyńska

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Karbowski, A. (2016). Shooting Methods to Solve Optimal Control Problems with State and Mixed Control-State Constraints. In: Szewczyk, R., Zieliński, C., Kaliczyńska, M. (eds) Challenges in Automation, Robotics and Measurement Techniques. ICA 2016. Advances in Intelligent Systems and Computing, vol 440. Springer, Cham. https://doi.org/10.1007/978-3-319-29357-8_17

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  • DOI: https://doi.org/10.1007/978-3-319-29357-8_17

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-29356-1

  • Online ISBN: 978-3-319-29357-8

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