jFuzzyLogic: a Java Library to Design Fuzzy Logic Controllers According to the Standard for Fuzzy Control Programming

Fuzzy Logic Controllers are a specific model of Fuzzy Rule Based Systems suitable for engineering applications for which classic control strategies do not achieve good results or for when it is too difficult to obtain a mathematical model. Recently, the International Electrotechnical Commission has published a standard for fuzzy control programming in part 7 of the IEC 61131 norm in order to offer a well defined common understanding of the basic means with which to integrate fuzzy control applications in control systems. In this paper, we introduce an open source Java library called jFuzzyLogic which offers a fully functional and complete implementation of a fuzzy inference system according to this standard, providing a programming interface and Eclipse plugin to easily write and test code for fuzzy control applications. A case study is given to illustrate the use of jFuzzyLogic.McGill Uninversity, Genome QuebecSpanish Government TIN2011-28488Andalusian Government P10-TIC-685

GRATE: A General Framework for Cooperative Problem Solving

As the deployment of expert systems has spread into more complex and sophisticated environments, so inherent technological limitations have been observed. As a technique for overcoming this complexity barrier, researchers have started to build systems composed of multiple, cooperating components. These systems tend to fall into two distinct categories: systems which solve a particular problem, such as speech recognition or vehicle monitoring, and systems which are general to some extent. GRATE is a general framework which enables an application builder to construct multi-agent systems for the domain of industrial process control. Unlike other cooperation frameworks, GRATE embodies a significant amount of inbuilt knowledge related to cooperation and control which can be utilised during system building. This approach offers a paradigm shift for the construction of multi-agent systems in which the role of configuring preexisting knowledge becomes an integral component. Rather than starting from scratch the designer can utilise the inbuilt knowledge and augment it, if necessary, with domain specific information. The GRATE architecture has a clear separation of concerns and has been applied to real-world problems in the domains of electricity transportation management and diagnosis of a particle accelerator beam controller

[[alternative]]混合模糊邏輯自子對線性解模糊輸出之探討

[[abstract]]The linear defuzzified output of a fuzzy controller with two fuzzy variable inputs and one output is discussed in this paper. Arbitrary amounts of triangular fuzzy numbers are employed to fuzzify the linguistic variables in fuzzy control rules. We show that the defuzzified output is exactly equivalent to a linear function of the inputs to the fuzzy controller by using three mixed fuzzy logic operators to evaluate the control rules.[[booktype]]紙