Titlebook: System Identification and Adaptive Control; Theory and Applicati Yiannis Boutalis,Dimitrios Theodoridis,Manolis A. Book 2014 Springer Inte

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1430-9491 for use in engineering systems.?All chapters are supported by illustrative simulation experiments, while separate chapters are devoted to the potential industrial applications of each model including projects 978-3-319-35412-5978-3-319-06364-5Series ISSN 1430-9491 Series E-ISSN 2193-1577

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Indirect Adaptive Control Based on the Recurrent Neurofuzzy Modelrameter and dynamic uncertainties, is considered in this chapter. The method is based on the new NF dynamical systems definition introduced in Chap.?., which uses the concept of adaptive fuzzy systems (AFS) operating in conjunction with recurrent high order neural networks. Since the plant is consid

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Direct Adaptive Neurofuzzy Control of SISO Systemscal form. Also, based on the same NF modeling, the adaptive tracking problem is addressed for the same class of affine nonlinear systems, which are exactly input-output linearizable by nonlinear state feedback. Following the approximation approach introduced in Sect.?, we consider that the unknown n

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