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- W2370604496 abstract "It is the foundation of process optimal control that builds accurately the whole thermal process model in all conditions. However thermal processes generally contain nonlinearity and randomicity, it is difficult to build the nonlinear models by the traditional method such as the transfer function,and so the whole optimal control for thermal processes is impossible. This paper proposesa kind of useful method by which the fuzzy rules based nonlinear models for thermal processes can be easily built. The method partitions the input data space into some local regions by the clustering and competitive learning algorithms firstly, then fuzzy rule baseddynamic linear model is built for each local region by the recursive least-square identification algorithm (RLS). Finally the whole thermal process model can accurately be described by a set of fuzzy rules based models. The computational results show that the proposed fuzzy rules based dynamic model can describe the non-linearity of processes accurately, and the relevant algorithms are very simple and usefu1." @default.
- W2370604496 created "2016-06-24" @default.
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- W2370604496 date "2002-01-01" @default.
- W2370604496 modified "2023-09-23" @default.
- W2370604496 title "A STUDY ON FUZZY RULES BASED AND NONLINEAR MODELS FOR THERMAL PROCESSES" @default.
- W2370604496 hasPublicationYear "2002" @default.
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