Abstract
The implementation of the inversion based linearizing method for the excitation system usually requires the full state feedback. This severely restricts its practical use because some of these states are very difficult to measure by physical sensors in practice due to no sensor available in the market or its high cost. To address this issue, the combined-inversion is proposed by coupling the left-inversion used as a soft-sensor with the right-inversion used as a nonlinear controller. Furthermore, to overcome the difficulty in explicit implementation of the combined-inversion by analytic means, an artificial neural network (ANN) is used to approximate the combined-inversion, thus forming the ANN combined-inversion. The simulation results demonstrate the effectiveness of the ANN combined-inversion.
This work is supported by the Natural Science Foundation of Hohai University (2007418111).
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Wang, WC. (2008). ANN Combined-Inversion Control for the Excitation System of Generator. In: Huang, DS., Wunsch, D.C., Levine, D.S., Jo, KH. (eds) Advanced Intelligent Computing Theories and Applications. With Aspects of Theoretical and Methodological Issues. ICIC 2008. Lecture Notes in Computer Science, vol 5226. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-87442-3_106
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DOI: https://doi.org/10.1007/978-3-540-87442-3_106
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