Abstract
The problem of controlling nonlinear dynamic systems has been the topic of many research projects in recent years. Nevertheless, there exist only a few approaches [9, 12, 15] that solve nonlinear control problems for a wide area of applications. Especially, intelligent tools like neural networks or fuzzy approaches can help solve these kinds of problems, but the amount of different learning algorithms, different fields of application and different objects makes it difficult to get a general overview of the features and limits of intelligent compositions.
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Straub, S. (2000). Dynamic Neural Network Compositions for Stable Identification of Nonlinear Systems with Known and Unknown Structures. In: Schröder, D. (eds) Intelligent Observer and Control Design for Nonlinear Systems. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-662-04117-8_12
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DOI: https://doi.org/10.1007/978-3-662-04117-8_12
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