Papers
Topics
Authors
Recent
Search
2000 character limit reached

Moving horizon estimation for nonlinear systems with time-varying parameters

Published 15 Apr 2024 in eess.SY and cs.SY | (2404.09566v1)

Abstract: We propose a moving horizon estimation scheme for estimating the states and time-varying parameters of nonlinear systems. We consider the case where observability of the parameters depends on the excitation of the system and may be absent during operation, with the parameter dynamics fulfilling a weak incremental bounded-energy bounded-state property to ensure boundedness of the estimation error (with respect to the disturbance energy). The proposed estimation scheme involves a standard quadratic cost function with an adaptive regularization term depending on the current parameter observability. We develop robustness guarantees for the overall estimation error that are valid for all times, and that improve the more often the parameters are detected to be observable during operation. The theoretical results are illustrated by a simulation example.

Definition Search Book Streamline Icon: https://streamlinehq.com
References (25)
  1. Min-max moving-horizon estimation for uncertain discrete-time linear systems. SIAM J. Control Optim., 50(3), 1439–1465.
  2. Moving-horizon state estimation for nonlinear discrete-time systems: New stability results and approximation schemes. Automatica, 44(7), 1753–1765.
  3. Robust stability of full information estimation. SIAM J. Control Optim., 59(5), 3472–3497.
  4. Nonlinear detectability and incremental input/output-to-state stability. SIAM J. Control Optim., 59(4), 3017–3039.
  5. A characterization of integral input-to-state stability. IEEE Trans. Autom. Control, 45(6), 1082–1097.
  6. Further equivalences and semiglobal versions of integral input to state stability. Dyn. Control, 10(2), 127–149.
  7. LMI design procedure for incremental input/output-to-state stability in nonlinear systems. IEEE Control Syst. Lett, 7, 3403–3408.
  8. Stable adaptive observers for nonlinear time-varying systems. IEEE Trans. Autom. Control, 33(7), 650–658.
  9. Adaptive observers for nonlinearly parameterized class of nonlinear systems. Automatica, 45(10), 2292–2299.
  10. Nonuniform observability for moving horizon estimation and stability with respect to additive perturbation. SIAM J. Control Optim., 61(5), 3018–3050.
  11. Strong ISS implies strong iISS for time-varying impulsive systems. Automatica, 122, 109224.
  12. Hu, W. (2024). Generic stability implication from full information estimation to moving-horizon estimation. IEEE Trans. Autom. Control, 69(2), 1164–1170.
  13. Robust Adaptive Control. Dover Publications, Inc., Mineola, NY, USA.
  14. Nonlinear full information and moving horizon estimation: Robust global asymptotic stability. Automatica, 150, 110603.
  15. Integral-input-to-state stability of switched nonlinear systems under slow switching. IEEE Trans. Autom. Control, 67(11), 5841–5855.
  16. Robust adaptive observers for nonlinear systems with bounded disturbances. IEEE Trans. Autom. Control, 45(6), 967–972.
  17. MHE under parametric uncertainty – robust state estimation without informative data. arXiv:2312.14049.
  18. Constrained state estimation for nonlinear discrete-time systems: stability and moving horizon approximations. IEEE Trans. Autom. Control, 48(2), 246–258.
  19. Model Predictive Control: Theory, Computation, and Design. Nob Hill Publish., LLC, Santa Barbara, CA, USA, 2nd edition. 3rd printing.
  20. A Lyapunov function for robust stability of moving horizon estimation. IEEE Trans. Autom. Control, 68(12), 7466–7481.
  21. Nonlinear moving horizon estimation for robust state and parameter estimation. arXiv:2312.13175.
  22. Moving horizon observer with regularisation for detectable systems without persistence of excitation. Int. J. Control, 84(6), 1041–1054.
  23. Adaptive observer design for discrete time LTV systems. Int. J. Control, 89(12), 2385–2395.
  24. Convergence guarantees for moving horizon estimation based on the real-time iteration scheme. IEEE Trans. Autom. Control, 59(8), 2215–2221.
  25. Bifurcation analysis and chaos control of the modified chua’s circuit system. Chaos Solit. Fractals, 77, 332–339.
Citations (1)
View on Semantic Scholar

Summary

No one has generated a summary of this paper yet.

Sign Up to Summarize

Paper to Video (Beta)

No one has generated a video about this paper yet.

Sign Up to Generate All Videos Subscribe on YouTube

Whiteboard

No one has generated a whiteboard explanation for this paper yet.

Sign Up to Generate

Open Problems

We haven't generated a list of open problems mentioned in this paper yet.

Generate Now

Continue Learning

We haven't generated follow-up questions for this paper yet.

Generate Now

Collections

Sign up for free to add this paper to one or more collections.

Sign Up