Results 181 to 190 of about 44,178 (218)
Some of the next articles are maybe not open access.
Fuzzy Components for Fuzzy Control
IFAC Proceedings Volumes, 1994Abstract Fuzzy components are characterized by their ability to handle fuzzy symbolic information. This paper presents their use in fuzzy control. First, we present a general typology of fuzzy controllers. Fuzzy components like fuzzy sensors, fuzzy actuators and fuzzy inference components are then defined. The use of fuzzy components in fuzzy control
L. Foulloy, S. Galichet, J.F. Josserand
openaire +1 more source
Journal of Biotechnology, 1992
This paper describes a fuzzy sets method which is very useful for handling uncertainties and essential for knowledge acquisition of a human expert. Kinetics of a reactor is often complex and not trivial to describe by mathematical equations. Reactor control by traditional control technology is therefore difficult. A novel technology is presented.
openaire +2 more sources
This paper describes a fuzzy sets method which is very useful for handling uncertainties and essential for knowledge acquisition of a human expert. Kinetics of a reactor is often complex and not trivial to describe by mathematical equations. Reactor control by traditional control technology is therefore difficult. A novel technology is presented.
openaire +2 more sources
Stability and the fuzzy controller
Fuzzy Sets and Systems, 1996The paper is devoted to the problem of stability of a single input-single output systems \(P\) put in a closed loop with a controller \((F)\). The main result states that if a system \((P,F)\) is stable then it is also stable for a number of elementary fuzzy controllers (FC) (including such commonly used as the Sugeno and Mamdani controller).
openaire +1 more source
1995
The paper presents fuzzy modelling as a tool for design of nonlinear controllers. An architecture and function of a fuzzy logic controller (FLC) is described. Three implementations of FLCs are recognized: look-up table, fuzzy relational and fuzzy logic-neural network based systems.
openaire +1 more source
The paper presents fuzzy modelling as a tool for design of nonlinear controllers. An architecture and function of a fuzzy logic controller (FLC) is described. Three implementations of FLCs are recognized: look-up table, fuzzy relational and fuzzy logic-neural network based systems.
openaire +1 more source
Fuzzy control of an underactuated robot with a fuzzy microcontroller
Microprocessors and Microsystems, 1999Abstract In this work the position control of a planar underactuated manipulator with two revolute joints is considered. A dynamic model of the system is presented and a fuzzy control strategy is proposed. Fuzzy logic allows empirical rules to be translated into a control algorithm.
openaire +2 more sources
Fuzzy Inference and Fuzzy Control
2009The major subject of this chapter is fuzzy control, one of the most successful application areas of fuzzy set theory. Nowadays, many fuzzy products are visible in the market. Almost every fuzzy product is related to a fuzzy control problem. It is no exaggeration to say that fuzzy set theory is highly accepted partly because of the great success of ...
Xuzhu Wang, Da Ruan, Etienne E. Kerre
openaire +1 more source
Fuzzy process control: construction of control charts with fuzzy numbers
Fuzzy Sets and Systems, 2005This paper presents the construction of fuzzy control charts for a process with fuzzy outcomes derived from the subjective quality ratings provided by a group of experts. The proposed fuzzy process control (FPC) methodology comprises an off-line stage and an on-line stage.
openaire +1 more source
1995
In this paper we argue that fuzzy controllers should be looked at as fuzzy valued mappings rather than crisp valued mappings. As a result using an explicit interpolation method as an inference mechanism becomes more natural than applying fuzzy reasoning.
openaire +1 more source
In this paper we argue that fuzzy controllers should be looked at as fuzzy valued mappings rather than crisp valued mappings. As a result using an explicit interpolation method as an inference mechanism becomes more natural than applying fuzzy reasoning.
openaire +1 more source