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To enhance the controller performance for the pneumatic system, in this paper, a hybrid adaptive neuro-fuzzy model reference is proposed.
The overall predictor effects in the validation data were re-estimated and compared with the reference overall predictor effects in the prediction model (reference is set to zero).
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The models' references are shown in Table 3.
The index given by the model of reference is here dropped for simplicity.
In this article, a systematically discrete dynamic sliding surface design methodology based on the model reference approach is presented.
Back then models for reference were expensive.
In both models the reference was randomly chosen, thus no assumptions were made on which amino acid or pair of amino acids constituted high or low risk.
Lastly, the experimental reference states are the bulk liquid phases of water and (CD3 2CO whereas the model reference states are a 19 H2O cluster and gas-phase (CD3 2CO.
A detailed listing of model data and references is provided in Additional file 1: Appendix A, Table A1.
A model reference control architecture is used to implement the model.
Model reference adaptive control is treated as adaptive tracking control on infinite horizon.
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