Abstract
Linear distributed parameter systems are an important family of models for many physical phenomena. A useful subfamily of these models is described by analytic semigroups, [14]. To model some perturbations or inaccuracies in these models it is often reasonable to introduce white noise in these systems to obtain linear stochastic distributed parameter systems. For controlled linear distributed parameter systems it is often natural to consider that the control occurs on the boundary or at discrete points because in many applications it is impractical or not feasible to apply the control throughout the domain.
Research partially supported by NSF Grants ECS-9102714 and DMS-9305936.
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Duncan, T.E. (1995). Some Results for the Adaptive Boundary Control of Stochastic Linear Distributed Parameter Systems. In: Åström, K.J., Goodwin, G.C., Kumar, P.R. (eds) Adaptive Control, Filtering, and Signal Processing. The IMA Volumes in Mathematics and its Applications, vol 74. Springer, New York, NY. https://doi.org/10.1007/978-1-4419-8568-2_3
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