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Creators/Authors contains: "Archibald, Richard"

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  1. ; ; ; (, Mathematics)
    This paper presents convergence analysis of a novel data-driven feedback control algorithm designed for generating online controls based on partial noisy observational data. The algorithm comprises a particle filter-enabled state estimation component, estimating the controlled system’s state via indirect observations, alongside an efficient stochastic maximum principle-type optimal control solver. By integrating weak convergence techniques for the particle filter with convergence analysis for the stochastic maximum principle control solver, we derive a weak convergence result for the optimization procedure in search of optimal data-driven feedback control. Numerical experiments are performed to validate the theoretical findings. 
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  2. ; ; ; (, SIAM Journal on Numerical Analysis)
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  3. ; ; (, Journal of Computational Physics)
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  4. ; ; ; ; ; ; ; ; ; ; et al (, SoftwareX)
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  5. ; (, Journal of Computational Physics)
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  6. ; ; (, Journal of Machine Learning for Modeling and Computing)
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  7. (, East Asian Journal on Applied Mathematics)
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  8. ; ; ; (, Journal of Scientific Computing)
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  9. ; ; (, Journal of Computational Physics)
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  10. ; ; ; (, Journal of Biomedical Optics)
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