Sergio García-Nieto

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— An extension of the model predictive control philosophy to the field of fuzzy control design is discussed. The main goal is to bring together the best features from both techniques. The basic idea is to divide the initial optimization problem in a set of recursive optimization subproblems or decision stages. Each subproblem is raised as a fuzzy LQR design(More)
— The main idea in this paper is to combine fuzzy controllers design with model predictive philosophy. In fact, this paper is an improvement of a previous work [1], where basic idea was to divide the initial optimization problem in a set of recursive optimization subproblems or decision stages. Each subproblem is raised as a fuzzy LQR design where the goal(More)
— MPC (Model Predictive Control) based on linear models is an extensively used methodology in the industrial field as a control solution for MIMO processes. The identification of ARX models for multivariable systems from input-output data often requires the use of LVMs (Latent Variable Methods) such as PCR (Principal Components Regression) or PLS (Partial(More)
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