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Descripción
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| In this work, a novel approach based on incremental state models has been proposed for the modeling of multivariable nonlinear delayed systems expressed by a generalized version of Takagi?Sugeno (T?S) fuzzy model. One of the key features of the new approach is that the proposed incremental state model compared with the no incremental one, naturally solves the problem of computing the target state, since for a desired output vector, a zero incremental state can be taken as an objective. Moreover, the control action in an incremental form is equivalent to introduce an integral action, thereby cancelling the steady state errors. Among other advantages using incremental models are the disappearance of the affine terms. Then, a fuzzy based linear quadratic regulator (FLC-LQR) is designed. Furthermore, a new optimal observer for multivariable fuzzy systems is developed, because not all states of the nonlinear system are fully available or measured. A multivariable thermal mixing tank system is chosen to evaluate the robustness of the proposed controller. The results obtained show a robust, well damped response with zero steady state error in the presence of disturbances and modeling errors. | |
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Internacional
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JCR del ISI
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Título de la revista
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Engineering Applications of Artificial Intelligence |
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ISSN
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0952-1976 |
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Factor de impacto JCR
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2,368 |
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Información de impacto
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Datos JCR del año 2015 |
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Volumen
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45 |
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DOI
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10.1016/j.engappai.2015.07.006 |
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Número de revista
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Desde la página
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259 |
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Hasta la página
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268 |
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Mes
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SIN MES |
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Ranking
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For 2015, the journal ENGINEERING APPLICATIONS OF ARTIFICIAL INTELLIGENC... has an Impact Factor of 2.368 in the following categories: AUTOMATION & CONTROL SYSTEMS; COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE; ENGINEERING, ELECTRICAL & ELECTRONIC; ENGINEERING, MULTIDISCIPLINARY; |