Abstract
In unit steam-boiler generation, a coordinated control strategy is required to ensure a higher rate of load change without violating thermal constraints. The process is characterized by nonlinearity and uncertainty. Using of neuro-fuzzy networks (NFNs) to represent a nonlinear dynamical process is one choice. Two alternative methods of exploiting the NFNs within a generalised predictive control (GPC) framework are described. Coordinated control of steam-boiler generation using the two nonlinear GPC methods show excellent tracking and disturbance rejection results.
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© 2007 Springer Berlin Heidelberg
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Liu, XJ., Liu, JZ. (2007). Neurofuzzy Power Plant Predictive Control. In: Liu, D., Fei, S., Hou, Z., Zhang, H., Sun, C. (eds) Advances in Neural Networks – ISNN 2007. ISNN 2007. Lecture Notes in Computer Science, vol 4492. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-72393-6_23
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DOI: https://doi.org/10.1007/978-3-540-72393-6_23
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-72392-9
Online ISBN: 978-3-540-72393-6
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