Abstract
In this chapter, we present the framework of operation of FCN, which is based on the adaptive estimation algorithms developed in the previous chapter and on the proposal of a fuzzy rule-based mechanism for storing acquired knowledge during its operation and training. Moreover, selected applications are presented, which demonstrate the applicability of the FCN framework both in conventional benchmark control problems and in real life applications. Both parameter adaptation algorithms, the linear and the bilinear one, are tested, emphasizing their distinct characteristics and advantages. The applications include the control of an inverted pendulum, the control of a hydroelectric power plant, and the coordination of different renewable power sources in order to yield an overall optimal power production and consumption in a smart grid application.
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\(B(h) = \left\{ {x \in \mathfrak {R}^n :\left| x \right| < h} \right\} \) is a ball centered at the origin \((0,0)\) with a radius of \(h\) and \({\left| \cdot \right| }\) is a norm on \(\mathfrak {R}^2\).
References
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Boutalis, Y., Theodoridis, D., Kottas, T., Christodoulou, M.A. (2014). Framework of Operation and Selected Applications. In: System Identification and Adaptive Control. Advances in Industrial Control. Springer, Cham. https://doi.org/10.1007/978-3-319-06364-5_10
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DOI: https://doi.org/10.1007/978-3-319-06364-5_10
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