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

Ricardo García Rosa, Teresa de Pedro Lucio (2000)

Mathware and Soft Computing

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 to be turned...

Forecasting return products in an integrated forward/reverse supply chain utilizing an ANFIS

D. Thresh Kumar, Hamed Soleimani, Govindan Kannan (2014)

International Journal of Applied Mathematics and Computer Science

Interests in Closed-Loop Supply Chain (CLSC) issues are growing day by day within the academia, companies, and customers. Many papers discuss profitability or cost reduction impacts of remanufacturing, but a very important point is almost missing. Indeed, there is no guarantee about the amounts of return products even if we know a lot about demands of first products. This uncertainty is due to reasons such as companies' capabilities in collecting End-of-Life (EOL) products, customers' interests...

Formal validation of fuzzy control techniques. Perspectives.

Antonio Sala, Pedro Albertos (1999)

Mathware and Soft Computing

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, uncertainty...

Further results on robust fuzzy dynamic systems with LMI 𝓓-stability constraints

Wudhichai Assawinchaichote (2014)

International Journal of Applied Mathematics and Computer Science

This paper examines the problem of designing a robust fuzzy controller with -stability constraints for a class of nonlinear dynamic systems which is described by a Takagi-Sugeno (TS) fuzzy model. Fuzzy modelling is a multi-model approach in which simple sub-models are combined to determine the global behavior of the system. Based on a linear matrix inequality (LMI) approach, we develop a robust fuzzy controller that guarantees (i) the ₂-gain of the mapping from the exogenous input noise to the...

Fuzzy and neural control of an induction motor

Mouloud Denai, Sid Attia (2002)

International Journal of Applied Mathematics and Computer Science

This paper presents some design approaches to hybrid control systems combining conventional control techniques with fuzzy logic and neural networks. Such a mixed implementation leads to a more effective control design with improved system performance and robustness. While conventional control allows different design objectives such as steady state and transient characteristics of the closed loop system to be specified, fuzzy logic and neural networks are integrated to overcome the problems with...

Fuzzy controller applications in stand-alone photovoltaic systems.

Joaquín Cañada Bago, Sebastián García Galán, Jorge Aguilera, Juan Ramón Velasco, Luis Magdalena (2002)

Mathware and Soft Computing

One of foremost problems in stand-alone photovoltaic systems consists on the election of a strategy for charge controllers. The charge controllers main function is the accumulation system protection, and this leads to an extension of the batteries lifetime, thus reducing the long term economic cost of the installation. This document describes a Fuzzy Logic based charge controller. In order to show the designed charge controller operation, firstly, a succession of simulations have been carried out...

Fuzzy controller for obstacle-avoidance with a non-holonomous mobile robot.

Uribe 1, Juan Pedro, Joseba Urzelai (1998)

Mathware and Soft Computing

This paper describes the design and development of a sensor based navigation system which makes it possible for a non-holonomous mobile robot to avoid obstacles using information on its environment picked up by a belt of ultrasonic sensors. To control the robot no preliminary information regarding its environment is required, the robot adapts to them through the information gathered on the spot by the ultrasonic sensors and the information released from a spatial memory. The controller, which allows...

Fuzzy empirical distribution function: Properties and application

Gholamreza Hesamian, S. M. Taheri (2013)

Kybernetika

The concepts of cumulative distribution function and empirical distribution function are investigated for fuzzy random variables. Some limit theorems related to such functions are established. As an application of the obtained results, a method of handling fuzziness upon the usual method of Kolmogorov-Smirnov one-sample test is proposed. We transact the α -level set of imprecise observations in order to extend the usual method of Kolmogorov-Smirnov one-sample test. To do this, the concepts of fuzzy...

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

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 Control...

Fuzzy logic gain scheduling for non-linear servo tracking

Mieczysław Brdyś, Jonathan Littler (2002)

International Journal of Applied Mathematics and Computer Science

This paper proposes the use of gain scheduling as a method of controlling a servo system with hard non-linear elements. The servo controls two elements of a tracker mounted on a ship at sea. There is stiction at the zero velocity point and non-linear friction against the motion of each tracker axis. A dual feedback loop control structure is employed. Fuzzy logic is used to provide smoothly varying non-linear scheduling functions to map the velocity of the servo relevant to the deck of the ship onto...

Fuzzy max-min classifiers decide locally on the basis of two attributes.

Birka von Schmidt, Frank Klawonn (1999)

Mathware and Soft Computing

Fuzzy classification systems differ from fuzzy controllers in the form of their outputs. For classification problems a decision between a finite number of discrete classes has to be made, whereas in fuzzy control the output domain is usually continuous, i.e. a real interval. In this paper we consider fuzzy classification systems using the max-min inference scheme and classifying an unknown datum on the basis of maximum matching, i.e. assigning it to the class appearing in the consequent of the rule...

Fuzzy-arithmetic-based Lyapunov synthesis in the design of stable fuzzy controllers: A computing-with-words approach

Changjiu Zhou (2002)

International Journal of Applied Mathematics and Computer Science

A novel approach to designing stable fuzzy controllers with perception-based information using fuzzy-arithmetic-based Lyapunov synthesis in the frame of computing with words (CW) is presented. It is shown that a set of conventional fuzzy control rules can be derived from the perception-based information using the standard-fuzzy-arithmetic-based Lyapunov synthesis approach. On the other hand, a singleton fuzzy controller can be devised by using a constrained-fuzzy-arithmetic-based Lyapunov synthesis...

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