Nonlinear Sampled-data Systems: A lifting framework

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  • Yamamoto, Yutaka
    Graduate School of Informatics, Kyoto University : Professor Emeritus
  • Yamamoto, Kaoru
    Faculty of Information Science and Electrical Engineering, Kyushu University

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  • Nonlinear Sampled-data Systems—A lifting framework

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This short note gives a new framework for dealing with nonlinear sampled-data systems. We introduce a new idea of lifting, which is well known for linear systems, but not successfully generalized to nonlinear systems. This paper introduces a new lifting technique for nonlinear, time-invariant systems, which are different from the linear counterpart as developed in Bamieh et al. (1991); Yamamoto (1994) etc. The main difficulty is that the direct feedthrough term effective in the linear case cannot be generalized to the nonlinear case. Instead, we will further lift the state trajectory, and obtain an equivalent time-invariant discrete-time system with function-space input and output spaces. The basic framework, as well as the closed-loop equation with discrete-time controller, is given. As an application of this framework, we give a representation for the Koopman operator derived from the given original nonlinear system.

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