Abstract-From 1992, Xfuzzy environment has been improving to ease the design of fuzzy systems. The current version, Xfuzzy 3, which is entirely programmed in Java, includes a wide set of new featured tools that allow automating the whole design process of a fuzzy logic based system: from its description (in the XFL3 language) to its synthesis in C, C++ or Java (to be included in software projects) or in VHDL (for hardware projects). The new features of the current version have been exploited in different application areas such as autonomous robot navigation and image processing.
Abstract-This paper proposes the design of hierarchical piecewise-affine (PWA) controllers to alleviate the processing time or prohibitive memory requirements of large controller structures. The constituent PWA modules of the hierarchical solution have fewer inputs and/or coarser partitions, so that they can reduce considerably the hardware resources required and/or the time response of the controller. A design methodology aided by CAD tools is employed to design the parameters of the controller, implement its architecture in an FPGA, and verify the static and dynamic behavior of the digital implementation by applying hardware-in-the-loop testing.
Abstract. Fuzzy models, traditionally used in the control field to model controllers or plants behavior, are used in this work to describe fingerprint images. The textures, in this case the directions of the fingerprint ridges, are described for the whole image by fuzzy if-then rules whose antecedents consider a part of the image and the consequent is the associated dominant texture. This low-level fuzzy model allows extracting higher-level information about the fingerprint, such as the existence of fuzzy singular points and their fuzzy position within the image. This is exploited in two applications: to provide comprehensive information for users of unattended automatic recognition systems and to extract linguistic patterns to classify fingerprints.
This paper presents a new form of Piecewise-Affine (PWA) solution, referred to as PWAH, to approximate the explicit Model Predictive Control (MPC) law, achieving a very rapid control response with the use of very few computational and memory resources. This is possible because PWAH controllers consist of Single-Input Single-Output (SISO) PWA modules connected in cascade so that the parameters needed to define them increase linearly instead of exponentially with the input dimension of the control problem. PWAH controllers are not universal approximators but several explicit MPC controllers can be efficiently approximated by them. A methodology to design PWAH controllers is presented and validated with application examples already solved by MPC approaches. The designed PWAH controllers implemented in Field Programmable Gate Arrays (FPGAs) provide the highest control speed using the fewest resources compared to the other digital implementations reported in the literature. Index Terms-Field-programmable gate arrays (FPGAs), hierarchical systems, model predictive control (MPC), piecewiseaffine (PWA) systems, PWA controllers.
Abstract-This paper describes a methodology to extract fuzzy models that describe linguistically the low-level features of an image (such as color, texture, etc.). The methodology combines grid-based algorithms with clustering and tabular simplification methods to compress image information into a small number of fuzzy rules with high linguistic meaning. All the steps of the methodology are carried out with the help offered by the tools of Xfuzzy 3 environment, so we can define, simplify, tune and verify the fuzzy models automatically. Several examples are included to illustrate the advantages of the methodology.
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