Abstract
In the last decade, there has been a large amount of activity in adaptive control of nonlinear systems using feedback linearization techniques ([104,128,165] and the references therein). The common assumptions in the literature are that the plant under study is affine, i.e., model is linear in the input variables and the nonlinearities are linearly parameterized by unknown parameters. However, many practical systems, e.g., chemical reactions and PH neutralization, are inherently nonlinear, whose input variables may not be expressed in an affine form.
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© 2002 Springer Science+Business Media New York
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Ge, S.S., Hang, C.C., Lee, T.H., Zhang, T. (2002). Non-affine Nonlinear Systems. In: Stable Adaptive Neural Network Control. The Springer International Series on Asian Studies in Computer and Information Science, vol 13. Springer, Boston, MA. https://doi.org/10.1007/978-1-4757-6577-9_6
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DOI: https://doi.org/10.1007/978-1-4757-6577-9_6
Publisher Name: Springer, Boston, MA
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