Displaying similar documents to “An intelligent ABS control based fuzzy logic. Aircraft application.”

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,...

First applications of the Orbex coprocessor: Control of unmanned vehicles.

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...

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...

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).

What is not clear in fuzzy control systems

Andrzej Piegat (2006)

International Journal of Applied Mathematics and Computer Science

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The paper presents a number of unclear, unsolved or partly solved problems of fuzzy logic, which hinder precise transformation of expert knowledge about proper control of a plant in a fuzzy controller. These vague problems comprise the realization of logical and arithmetic operations and another basic problem, i.e., the construction of membership functions. The paper also indicates how some of the above problems can be solved.

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...