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2. A fuzzy model of power supply system controlJanez Usenik, 2012, original scientific article Abstract: In this article, a mathematical model of control of a dynamic system is described; one such system could be a power supply system. Analytical approaches that have been developed to describe the influence of production and stock, i.e. additional capacities, require a hierarchical spatial pattern and demand. Demand is usually an inherently stochastic process, but in this article we simulate it as an output fuzzy variable in a fuzzy system, in which all the input variables are also fuzzy. Furthermore, an interesting use of neural sets is shown, which is presented as an efficient method for the optimisation of the fuzzy system. At the end, a numerical example is given.
Keywords: power supply system, energy capacities, demand, fuzzy logic, neural net
Published in DKUM: 10.07.2015; Views: 2472; Downloads: 33
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7. Decomposed fuzzy proportional-integral-derivative controllersMarjan Golob, 2001, original scientific article Abstract: In this paper, several types of decomposed proportional-integral-derivative fuzzy logic controllers (PID FLCs) are tested and compared. An important feature of decomposed PID FLCs are their simple structures. In its simplest version, the decomposed PID FLC uses three one-input one-output inferences with three separate rule bases. Behaviours of proportional, integral and derivative PID FLC parts are defined with simple rules in proportional rule base, integral rule base and derivative rule base. The proposed decomposed PID FLC has been compared with several PID FLCs structures. All PID FLCs have been realised by the same hardware and software tools and have been applied as a real-time controller to a simple magnetic suspension system.
Keywords: fuzzy logic control, PID control, decomposed fuzzy system, magnetic suspension system
Published in DKUM: 01.06.2012; Views: 2148; Downloads: 111
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10. Fuzzy logic based quality monitoring in short-circuit gas metal arc weldingMarjan Golob, Arpad Köveš, 2007, original scientific article Abstract: Conventional methods, e.g. destructive and non-destructive testing methods, are expensive and time-consuming; therefore, possibilities of online and automated quality control of a welding process during welding as such are investigated. The paper deals with the possibilities of application of fuzzy logic to the analysis of weld quality, particularly assessment of the weld surface condition by means of measurable electric signals emitted during welding. A simple fuzzy inference system was realised which could relatively efficiently assess the weld quality on the basis of time variations of the welding voltage and short-circuit time in a certain time window.
Keywords: fuzzy systems, fuzzy logic, gas metal arc welding, GMAW, quality monitoring, statistical analysis, quality control, weld quality
Published in DKUM: 31.05.2012; Views: 2504; Downloads: 105
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