Optimization based on quasi-Monte Carlo sampling to design state estimators for non-linear systems

DOI10.1080/02331930902863665zbMath1206.11097OpenAlexW2069095001MaRDI QIDQ3066914

Angelo Alessandri, Danilo Macciò, Cristiano Cervellera, Marcello Sanguineti

Publication date: 20 January 2011

Published in: Optimization (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1080/02331930902863665

zbMATH Keywords

state estimationconstrained optimizationinput-to-state stabilityquasi-Monte Carlo methodslow-discrepancy sequencesnon-linear programmingridge computational models

Mathematics Subject Classification ID

Related Items (4)

Minimizing sequences for a family of functional optimal estimation problems ⋮ Robust fault estimation based on learning observer for Takagi‐Sugeno fuzzy systems with interval time‐varying delay ⋮ Adaptive fuzzy output feedback backstepping control of pure‐feedback nonlinear systems via dynamic surface control technique ⋮ On Hamilton-Jacobi approaches to state reconstruction for dynamic systems

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