Rinaldo Poluzzi

Automatic synthesis, analysis and implementation of a fuzzy controller

A method based on the cell-to-cell approach is proposed for extracting the control rules for a fuzzy controller. This procedure was implemented to control the position of a DC motor. To obtain high performance in terms of fuzzy inferences per second (FIPS) that complex control requires, the rules and the membership functions have been implemented via a hardware solution, WARP. WARP is a dedicated VLSI machine with an architecture designed to efficiently exploit data provided by the cell-to-cell approach. The global architecture along with some generalities on the particular approach are presented.<<ETX>>

Synthesis of fuzzy controllers through neural networks

Abstract Most of the current fuzzy logic control applications are designed using different heuristics for the controller synthesis, and then implemented using conventional programming languages on general purpose microcontrollers. We are proposing a methodology for the design of fuzzy controllers based on the cell-to-cell mapping approach for the fuzzy control law synthesis, and on neural networks for: (a) the discovery of the set of appropriate fuzzy rules that characterise a control law, and (b) the tuning of parameters that characterise membership functions (namely position and width). We suppose that training data are coming from sampling of the analytical control function. Two examples are shown, and a comparison with the results obtained by a generalized multilayer perceptron is discussed.

A fuzzy decision directed filter for impulsive noise reduction

Abstract In this paper a fuzzy filter for the impulsive noise reduction is presented. A fuzzy system has been developed to detect noise configurations and then a classical filter is activated depending on the output of a structure extraction process.

A new postprocessing algorithm to reduce artifacts in block-coded images

This paper presents a new non-linear adaptive filter for blocking artefacts reduction of images coded with block-based compression standards. Fuzzy logic has been used to develop this filter.

Neuro-fuzzy clustering techniques for complex acoustic scenarios

An apparatus is described capable of detecting a specific sound among a sound mixture and of identifying the environmental acoustic scenario, to automatically adapt the apparatus to changing environmental conditions. Such an apparatus could be useful, for example, in the design of an ASR system robust to environmental noise. Starting from a time-frequency representation of the incoming signal, neuro-fuzzy clustering is performed on proper features extracted from time-frequency objects.

Fuzzy logic based image processing in IQTV environment

In this paper, new filtering techniques for TV quality improvement are presented. Fuzzy logic has been used to develop non-linear filters for impulsive and Gaussian noise reduction, scanning rate conversion and detail visibility enhancement. >

DC/DC converters fuzzy control

This paper aims to illustrate the use of a sophisticated methodology, based on system simulation techniques, to design a fuzzy controller for a DC/DC converter. The goal of the control is to stabilize the voltage output of the switching regulator against the load and parametric variations for a flyback topology. This system is characterized by being unstable in closed loop configuration. Robustness and high performances art requested to the control law especially for high power systems (more than 200 Watt). In order to obtain a good cost/performances ratio, the rules and the related membership functions have to be implemented via an analog dedicated solution capable to obtain an elevated number of FIPS (fuzzy inference per second).<<ETX>>

Hardware and Software Architectures for Soft Computing

The paper aims to present well-described examples of VLSI-dedicated architectures for soft computing applications in terms of performances and internal functional structure. In addition, closely connected to the described hardware components, an example of a Neuro-Fuzzy software architecture able to perform a system identification process on available measurements, is presented with some reference applications.

Integrated development environment for fuzzy logic applications

During the last five years, Fuzzy Logic has gained enormous popularity, both in the academic and industrial worlds, breaking up the traditional resistance against changes thanks to its innovative approach to problems formalization. The success of this new methodology is pushing the creation of a brand new class of devices, called Fuzzy Machines, to overcome the limitations of traditional computing systems when acting as Fuzzy Systems and adequate Software Tools to efficiently develop new applications. This paper aims to present a complete development environment for the definition of fuzzy logic based applications. The environment is also coupled with a sophisticated software tool for semiautomatic synthesis and optimization of the rules with stability verifications. Later it is presented the architecture of WARP, a dedicate VLSI programmable chip allowing to compute in real time a fuzzy control process. The article is completed with two application examples, which have been carried out exploiting the aforementioned tools and devices.© (1993) COPYRIGHT SPIE--The International Society for Optical Engineering. Downloading of the abstract is permitted for personal use only.