Displaying similar documents to “Adaptive fuzzy tracking control for a permanent magnet synchronous motor via backstepping approach.”

Fuzzy feedback linearizing controller and its equivalence with the fuzzy nonlinear internal model control structure

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...

Cooperative-corrector multivariable fuzzy controller.

M.ª Cristina Rivero, P. Lasso, Félix Monasterio-Huelin (1998)

Mathware and Soft Computing

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This paper deals with the decomposition problem of a multivariable fuzzy controller. For this purpose, the use of notions taken from the framework of the Game Theory is proposed. Using the notion of couple between variables, a partition of the rule space in subsystems is obtained. The subsystems are considered players that correct the actions of the others. These ideas are applied to the control of a polymerization reactor (CSTR).

Indirect adaptive controller based on a self-structuring fuzzy system for nonlinear modeling and control

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...

Evolutionary optimization of interval mathematics-based design of a TSK fuzzy controller for anti-sway crane control

Jarosław Smoczek (2013)

International Journal of Applied Mathematics and Computer Science

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A hybrid method combining an evolutionary search strategy, interval mathematics and pole assignment-based closed-loop control synthesis is proposed to design a robust TSK fuzzy controller. The design objective is to minimize the number of linear controllers associated with rule conclusions and tune the triangular-shaped membership function parameters of a fuzzy controller to satisfy stability and desired dynamic performances in the presence of system parameter variation. The robust performance...

Formal validation of fuzzy control techniques. Perspectives.

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,...

Robust adaptive fuzzy filters output feedback control of strict-feedback nonlinear systems

Shaocheng Tong, Changliang Liu, Yongming Li (2010)

International Journal of Applied Mathematics and Computer Science

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In this paper, an adaptive fuzzy robust output feedback control approach is proposed for a class of single input single output (SISO) strict-feedback nonlinear systems without measurements of states. The nonlinear systems addressed in this paper are assumed to possess unstructured uncertainties, unmodeled dynamics and dynamic disturbances, where the unstructured uncertainties are not linearly parameterized, and no prior knowledge of their bounds is available. In recursive design, fuzzy...