Approximate Sampled-Data Models for Nonlinear Stochastic Systems
In this chapter the ideas in Chap. 16 are extended to obtain approximate sampled models for stochastic nonlinear systems. In particular, the concepts of time-domain approximate stochastic sampled models based on up-sampling and successive integration are extended to the nonlinear case.
KeywordsStochastic Differential Equation Approximate Model Nonlinear Case Successive Integration Stochastic Nonlinear System
The use of up-sampling in the context of nonlinear filtering is discussed in
- Cea M, Goodwin GC, Müller C (2011) A novel technique based on up-sampling for addressing modeling issues in sampled data nonlinear filtering. In: 18th IFAC world congress, Milan, Italy Google Scholar
Conditions for existence of diffeomorphisms that transform stochastic linear systems to different canonical forms can be found in
The extension of one-step convergence errors to fixed-step convergence errors and the proof of Theorem 18.5 first appeared in
- Carrasco DS (2014) PhD thesis, University of Newcastle, Australia (in preparation) Google Scholar