Details
| Original language | English |
|---|---|
| Pages (from-to) | 19 - 24 |
| Number of pages | 6 |
| Journal | IEEE Control Systems Letters |
| Volume | 7 |
| Publication status | Published - 24 Jun 2022 |
Abstract
We propose a suboptimal moving horizon estimation (MHE) scheme for a general class of nonlinear systems. To this end, we consider an MHE formulation that optimizes over the trajectory of a robustly stable observer. Assuming that the observer admits a Lyapunov function, we show that this function is an M-step Lyapunov function for suboptimal MHE. The presented sufficient conditions can be easily verified in practice. We illustrate the practicability of the proposed suboptimal MHE scheme with a standard nonlinear benchmark example. Here, performing a single iteration is sufficient to significantly improve the observer's estimation results under valid theoretical guarantees.
Keywords
- Estimation, Lyapunov methods, Moving horizon estimation (MHE), Observers, Standards, System dynamics, Time-varying systems, Trajectory, nonlinear systems, stability, state estimation
ASJC Scopus subject areas
- Engineering(all)
- Control and Systems Engineering
- Mathematics(all)
- Control and Optimization
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In: IEEE Control Systems Letters, Vol. 7, 24.06.2022, p. 19 - 24.
Research output: Contribution to journal › Article › Research › peer review
}
TY - JOUR
T1 - A simple suboptimal moving horizon estimation scheme with guaranteed robust stability
AU - Schiller, Julian D.
AU - Wu, Boyang
AU - Muller, Matthias A.
N1 - This work was supported by the German Research Foundation (DFG) under Grant MU 3929/2-1.
PY - 2022/6/24
Y1 - 2022/6/24
N2 - We propose a suboptimal moving horizon estimation (MHE) scheme for a general class of nonlinear systems. To this end, we consider an MHE formulation that optimizes over the trajectory of a robustly stable observer. Assuming that the observer admits a Lyapunov function, we show that this function is an M-step Lyapunov function for suboptimal MHE. The presented sufficient conditions can be easily verified in practice. We illustrate the practicability of the proposed suboptimal MHE scheme with a standard nonlinear benchmark example. Here, performing a single iteration is sufficient to significantly improve the observer's estimation results under valid theoretical guarantees.
AB - We propose a suboptimal moving horizon estimation (MHE) scheme for a general class of nonlinear systems. To this end, we consider an MHE formulation that optimizes over the trajectory of a robustly stable observer. Assuming that the observer admits a Lyapunov function, we show that this function is an M-step Lyapunov function for suboptimal MHE. The presented sufficient conditions can be easily verified in practice. We illustrate the practicability of the proposed suboptimal MHE scheme with a standard nonlinear benchmark example. Here, performing a single iteration is sufficient to significantly improve the observer's estimation results under valid theoretical guarantees.
KW - Estimation
KW - Lyapunov methods
KW - Moving horizon estimation (MHE)
KW - Observers
KW - Standards
KW - System dynamics
KW - Time-varying systems
KW - Trajectory
KW - nonlinear systems
KW - stability
KW - state estimation
UR - http://www.scopus.com/inward/record.url?scp=85133661918&partnerID=8YFLogxK
U2 - 10.48550/arXiv.2203.16090
DO - 10.48550/arXiv.2203.16090
M3 - Article
VL - 7
SP - 19
EP - 24
JO - IEEE Control Systems Letters
JF - IEEE Control Systems Letters
ER -