Skip to main content
Log in

Sensitivity analysis for parametric control problems with control-state constraints

  • Published:
Computational Optimization and Applications Aims and scope Submit manuscript

Abstract

Parametric nonlinear control problems subject to vector-valued mixed control-state constraints are investigated. The model perturbations are implemented by a parameter p of a Banach-space P. We prove solution differentiability in the sense that the optimal solution and the associated adjoint multiplier function are differentiable functions of the parameter. The main assumptions for solution differentiability are composed by regularity conditions and recently developed second-order sufficient conditions (SSC). The analysis generalizes the approach in [16, 20] and establishes a link between (1) shooting techniques for solving the associated boundary value problem (BVP) and (2) SSC. We shall make use of sensitivity results from finite-dimensional parametric programming and exploit the relationships between the variational system associated to BVP and its corresponding Riccati equation.

Solution differentiability is the theoretical backbone for any numerical sensitivity analysis. A numerical example with a vector-valued control is presented that illustrates sensitivity analysis in detail.

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

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Similar content being viewed by others

References

  1. H.G.Bock, “Zur numerischen Behandlung zustandsbeschränkter Steuerungsprobleme mit Mehrzielmethode und Homotopieverfahren,” ZAMM, vol. 57, pp. 266–268, 1990.

    Google Scholar 

  2. H.G.Bock and P.Krämer-Eis, “An efficient algorithm for approximate computation of feedback control laws in nonlinear processes,” ZAMM, vol. 61, pp. 330–332, 1981.

    Google Scholar 

  3. R. Bulirsch, “Die Mehrzielmethode zur numerischen Lösung von nichtlinearen Randwertproblemen und Aufgaben der optimalen Steuerung,” Report of the Carl-Cranz Gesellschaft, Oberpfaffenhofen, 1971.

  4. D.J.Clements and B.D.O.Anderson, Singular optimal control: The linear-quadratic problem, Lecture Notes in Control and Information Sciences, vol. 5, Springer-Verlag: Berlin, 1978.

    Google Scholar 

  5. A.L.Dontchev and W.W.Hager, “Lipschitz stability in nonlinear control and optimization,” SIAM J. Control and Optimization, vol. 31, pp. 569–603, 1993.

    Google Scholar 

  6. A.L.Dontchev, W.W.Hager, A.B.Poore, and B.Yang, “Optimality, stability and convergence in nonlinear control,” Applied Math. Optim., vol. 31, pp. 569–603, 1995.

    Google Scholar 

  7. A.V.Fiacco, Introduction to Sensitivity and Stability Analysis in Nonlinear Programming, Academic Press: New York, 1983.

    Google Scholar 

  8. W.W.Hager, “Lipschitz continuity for constrained processes,” SIAM J. Control and Optimization, vol. 17, pp. 321–336, 1979.

    Google Scholar 

  9. E.V.Haynsworth, “Determination of the inertia of a partitioned Hermitian matrix,” Linear Algebra and Applications, vol. 1, pp. 73–81, 1968.

    Google Scholar 

  10. K.Ito and K.Kunisch, “Sensitivity analysis of solutions to optimization problems in Hilbert spaces with applications to optimal control and estimation,” Journal of Differential Equations, vol. 99, pp. 1–40, 1992.

    Google Scholar 

  11. P. Krämer-Eis, “Ein Mehrzielverfahren zur numerischen Berechnung optimaler Feedback-Steuerungen bei beschränkten nichtlinearen Steuerungsproblemen,” Bonner Mathematische Schriften, vol. 164, 1985.

  12. B.Kugelmann and H.J.Pesch, “A new general guidance method in constrained optimal control, Part 1: Numerical method,” J. Optim. Theory and Appl., vol. 67, pp. 421–435, 1990.

    Google Scholar 

  13. B.Kugelmann and H.J.Pesch, “A new general guidance method in constrained optimal control, Part 2: Application to space shuttle guidance,” J. Optim. Theory and Appl., vol. 67, pp. 437–446, 1990.

    Google Scholar 

  14. K.Malanowski, “Sensitivity analysis of optimization problems in Hilbert space with application to optimal control,” Appl. Math. Optim., vol. 21, pp. 1–20, 1990.

    Google Scholar 

  15. K.Malanowski, “Second order conditions and constraint qualifications in stability and sensitivity analysis of solutions to optimization problems in Hilbert spaces,” Applied Math. Optim., vol. 25, pp. 51–79, 1992.

    Google Scholar 

  16. K.Malanowski, “Two-norm approach in stability and sensitivity analysis of optimization and optimal control problems,” Advances in Math. Sciences and Applications, vol. 2, pp. 397–443, 1993.

    Google Scholar 

  17. K.Malanowski, “Stability and sensitivity of solutions to nonlinear optimal control problems.” Appl. Math. Optim., vol. 32, pp. 111–141, 1994.

    Google Scholar 

  18. K.Malanowski, “Regularity of solutions in stability analysis of optimization and optimal control problems,” Control and Cybernetics, vol. 23, pp. 61–86, 1994.

    Google Scholar 

  19. H.Maurer and H.J.Pesch, “Solution differentiability for parametric nonlinear control problems,” SIAM Journal on Control and Optimization, vol. 32, pp. 1542–1554, 1994.

    Google Scholar 

  20. H.Maurer and H.J.Pesch, “Solution differentiability for parametric nonlinear control problems with control-state constraints,” Control and Cybernetics, vol. 23, pp. 201–227, 1994.

    Google Scholar 

  21. H.Maurer and S.Pickenhain, “Second order sufficient conditions for optimal control problems with mixed control-state constraints,” Journal of Optimization Theory and Applications, vol. 86, pp. 649–667, 1995.

    Google Scholar 

  22. L.W.Neustadt, Optimization: A Theory of Necessary Conditions, Princeton University Press: Princeton, 1976.

    Google Scholar 

  23. H.J.Oberle and W.Grimm, “BNDSCO—A program for the numerical solution of optimal control problems,” Institute for Flight Systems Dynamics, DLR, Oberpfaffenhofen, Germany, Internal Report No. 515–89/22, 1989.

    Google Scholar 

  24. H.J.Pesch, “Real-time computation of feedback controls for constrained optimal control problems, Part 1: Neighbouring extremals,” Optimal Control Applications & Methods, vol. 10, pp. 129–145, 1989.

    Google Scholar 

  25. H.J.Pesch, “Real-time computation of feedback controls for constrained optimal control problems, Part 2: A correction method based on multiple shooting,” Optimal Control Applications & Methods, vol. 10, pp. 147–171, 1989.

    Google Scholar 

  26. S.Pickenhain, “Sufficiency conditions for weak local minima in multidimensional optimal control problems with mixed control-state restrictions,” Zeitschrift für Analysis und ihre Anwendungen, vol. 11, pp. 559–568, 1992.

    Google Scholar 

  27. W.T.Reid, Riccati Differential Equations, Mathematics in Science and Engineering, vol. 86, Academic Press: New York, 1972.

    Google Scholar 

  28. S.M.Robinson, “Local structure of feasible sets in nonlinear programming, Part III: Stability and sensitivity,” Mathematical Programming Study, vol. 30, pp. 45–66, 1987.

    Google Scholar 

  29. V.Zeidan, “The Riccati equation for optimal control problems with mixed state-control constraints: Necessity and sufficiency,” SIAM J. Control and Optimization, vol. 32, pp. 1297–1321, 1994.

    Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Rights and permissions

Reprints and permissions

About this article

Cite this article

Malanowski, K., Maurer, H. Sensitivity analysis for parametric control problems with control-state constraints. Comput Optim Applic 5, 253–283 (1996). https://doi.org/10.1007/BF00248267

Download citation

  • Received:

  • Revised:

  • Issue Date:

  • DOI: https://doi.org/10.1007/BF00248267

Keywords

Navigation