GA-based fuzzy sliding mode controller for nonlinear systems.
Chen, P.C., Chen, C.W., Chiang, W.L. (2008)
Mathematical Problems in Engineering
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Chen, P.C., Chen, C.W., Chiang, W.L. (2008)
Mathematical Problems in Engineering
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Yeh, Ken, Chen, Cheng-Wu (2010)
Mathematical Problems in Engineering
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Ricardo García Rosa, Teresa de Pedro Lucio (2000)
Mathware and Soft Computing
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The ORBEX coprocessor has been designed to execute the typical fuzzy operations of a system based on fuzzy rules. The first real application has been fuzzy controllers for electric cars. The values of the input variables, the position and the orientation of the car with respect the desired trajectory of reference, are obtained from the data provided by a DGPS boarded in the vehicle. The values of the output variables provided by the controller are the angle that the steering wheel has...
Amaral Mozelli, Leonardo, Martinez Palhares, Reinaldo (2011)
Mathematical Problems in Engineering
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Wudhichai Assawinchaichote (2014)
International Journal of Applied Mathematics and Computer Science
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Vladimir Pavlica, Dušan Petrovački (1999)
The Yugoslav Journal of Operations Research
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Antonio Sala, Pedro Albertos (1999)
Mathware and Soft Computing
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In this paper, a survey of the state of the art and perspectives of two main lines of research in fuzzy control systems is presented: on one hand, the navas interpolative-functional line representing fuzzy systems as parameterized universal function approximators, thus applying nonlinear control and neural network paradigms; on the other hand, a logic-formal approach where fuzzy systems are analysed in terms of logic interpretations, exploring validation, consistency and completeness,...
Reda Boukezzoula, Sylvie Galichet, Laurent Foulloy (2007)
International Journal of Applied Mathematics and Computer Science
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This paper examines the inverse control problem of nonlinear systems with stable dynamics using a fuzzy modeling approach. Indeed, based on the ability of fuzzy systems to approximate any nonlinear mapping, the nonlinear system is represented by a Takagi-Sugeno (TS) fuzzy system, which is then inverted for designing a fuzzy controller. As an application of the proposed inverse control methodology, two popular control structures, namely, feedback linearization and Nonlinear Internal Model...
Ruiyun Qi, Mietek A. Brdys (2009)
International Journal of Applied Mathematics and Computer Science
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In this paper, a unified nonlinear modeling and control scheme is presented. A self-structuring Takagi-Sugeno (T-S) fuzzy model is used to approximate the unknown nonlinear plant based on I/O data collected on-line. Both the structure and the parameters of the T-S fuzzy model are updated by an on-line clustering method and a recursive least squares estimation (RLSE) algorithm. The rules of the fuzzy model can be added, replaced or deleted on-line to allow a more flexible and compact...
Haiping Du, Nong Zhang (2010)
Control and Cybernetics
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Thomas Möllers (1999)
Acta Mathematica et Informatica Universitatis Ostraviensis
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