Inmaculada García-Moral

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Neurofuzzy networks are hybrid systems that combine neural networks with fuzzy systems, and the Adaptive Neuro-Fuzzy inference system (ANFIS) is a particular case in which a fuzzy system is implemented in the framework of an adaptive neural network. This neurofuzzy approach represents an effective structure to the modeling of plant dynamics, and the(More)
A stabilization method based on the input-output conicity criterion is presented. Conventional learning algorithms are applied to adjust the controller dynamics, and robust stability of the closed-loop system is guaranteed by modifying the training patterns which yield unstable behavior. The methodology developed expands the class of nonlinear systems to be(More)
In the present paper. nrural control and idrnlilicdtian of general nonlinear plants are accomplished using radial basis function (RBF) networks. A neural controller is ad~ustcd oil-line by casing the orthogonal least squares (OLS) method. A stability analysis has been perfhrmcd using the conicity criterion. and based upon this a nw training data set is(More)
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