Fuzzy Control Based on Fuzzy Relation Equations
Fuzzy controller applications in stand-alone photovoltaic systems.
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 design based on stability criteria
Fuzzy controller for obstacle-avoidance with a non-holonomous mobile robot.
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
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 -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
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
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.
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 membership function generation using particle swarm optimization.
Fuzzy Model of the Computer Integrated Decision Support and Management System in Mineral Processing
Fuzzy modelling of temperature difference in 200 MW power unit condenser using genetic fuzzy systems
Fuzzy Short-Run Control Charts.
Fuzzy system reliability analysis
Fuzzy-arithmetic-based Lyapunov synthesis in the design of stable fuzzy controllers: A computing-with-words approach
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...
GA-based fuzzy sliding mode controller for nonlinear systems.
Goodman-Kruskal Measure of Association for Fuzzy-Categorized Variables
The Goodman-Kruskal measure, which is a well-known measure of dependence for contingency tables, is generalized to the case when the variables of interest are categorized by linguistic terms rather than crisp sets. In addition, to test the hypothesis of independence in such contingency tables, a novel method of decision making is developed based on a concept of fuzzy -value. The applicability of the proposed approach is explained using a numerical example.
Hierarchical decomposition of fuzzy controllers based on meta-knowledge.
This paper focuses on the problem of decomposing multivariable fuzzy controllers using a hierarchical approach based on the application of meta-knowledge. Usually, hierarchical fuzzy systems are based on a cascade structure of fuzzy logic controllers where the output of each level is considered as one of the inputs to the following level. The paper introduces a different approach to the idea of hierarchy, where the output of a level is considered not as input to the following level controller but...
Improved fuzzy feedback linearization and Sinswat-transformation control of inverted pendulum
Improved results on fuzzy filter design for T-S fuzzy systems.
Indirect adaptive controller based on a self-structuring fuzzy system for nonlinear modeling and control
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 model structure....