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Fuzzy network model-based fuzzy state controller design
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DOI：10.1109/91.873586.png)
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Abstract
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The performance of model-based controller design relies heavily on the quality and suitability of the utilized process model. This contribution proposes a fuzzy network based nonlinear controller design methodology. Fuzzy networks are a model approach combining high approximation quality with high interpretability. The input/output (I/O) models commonly used for identification are transformed to fuzzy state-space models, Transferring and adjusting methods from linear state-space theory a control concept consisting of a fuzzy state controller and an adaptive set-point filter for nonlinear dynamic processes is deduced. The capability of the method is demonstrated for a hydraulic drive.
Keywords:
adaptive set-point filtering
fuzzy control
fuzzy models
fuzzy networks
fuzzy state-space controller
hydraulic drives
nonlinear control
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