Summary
This chapter discusses a new method for applying neural networks to control of nonlinear systems. Contrast to a conventional method, the new method does not use neural network directly as a nonlinear controller or nonlinear prediction model, but use it indirectly via an ARX-like macro-model, in which neural network is embedded. The ARX-like model incorporating neural network is constructed in such a way that it has similar linear properties to a linear ARX model. The nonlinear controller is then designed in a similar way as designing a controller based on a linear ARX model. Numerical examples are used to illustrate the usefulness of the new method.
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Hu, J., Hirasawa, K. (2004). A Method for Applying Neural Networks to Control of Nonlinear Systems. In: Rajapakse, J.C., Wang, L. (eds) Neural Information Processing: Research and Development. Studies in Fuzziness and Soft Computing, vol 152. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-39935-3_19
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DOI: https://doi.org/10.1007/978-3-540-39935-3_19
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