Abstract
In this article, we introduce some recent results on the complexity of the model and controller using a unified probabilistic approach to model estimation/selection and controller design. The objective systems are assumed to include unknown random parameters with probability distributions. The first issue is what evaluation function, for model estimation, is reasonable with respect to the controller design. Second, we analyse the effects of the complexity of the parameter distribution model and the class of controller on the expectation of the evaluation functions for model estimation. Finally, we discuss the distribution of systems with a result on a metric structure of a set of analytic functions.
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Tsumura, K. (2003). Complexity of Systems and Controllers. In: Hashimoto, K., Oishi, Y., Yamamoto, Y. (eds) Control and Modeling of Complex Systems. Trends in Mathematics. Birkhäuser, Boston, MA. https://doi.org/10.1007/978-1-4612-0023-9_10
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DOI: https://doi.org/10.1007/978-1-4612-0023-9_10
Publisher Name: Birkhäuser, Boston, MA
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