Abstract
The paper deals with the Neuro-fuzzy model-based control and its application. Various types of the fuzzy logic and neural-net-based nonlinear autoregressive models with exogenous variables are reviewed with respect to the model error. Two types of model-based neuro-fuzzy control – a cancellation controller and a predictive controller are reviewed – and the robustness issues of such control are discussed. Finally, the application of the proposed design method to a laboratory scale heat exchanger is given.
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Matko, D., Kavšek-Biasizzo, K. & Kocijan, J. Neuro-fuzzy Model-based Control. Journal of Intelligent and Robotic Systems 23, 249–265 (1998). https://doi.org/10.1023/A:1008071130242
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DOI: https://doi.org/10.1023/A:1008071130242