Microelectronic Design of Fuzzy Logic-Based Systems

Summary

Fuzzy logic has virtually exploded over the landscape of emerging technologies, becoming an integral part of myriad applications and a standard tool for engineers. Until recently, most of the attention and applications have centered on fuzzy systems implemented in software. But these systems are limited. Problems that require real-time operation, low area, or low power consumption demand hardware designed to the fuzzy paradigm - and engineers with the background and skills to design it.

Microelectronic Design of Fuzzy Logic-Based Systems offers low-cost answers to issues that software cannot resolve. From the theoretical, architectural, and technological foundation to design tools and applications, it serves as your guide to effective hardware realizations of fuzzy logic.

Review fuzzy logic theory and the basic issues of fuzzy sets, operators, and inference mechanisms

Explore the trade-offs between efficient theoretical behavior and practical hardware realizations

Discover the properties of the possible microelectronic realizations of fuzzy systems - conventional processors, fuzzy coprocessors, and fuzzy chips

Investigate the design of fuzzy chips that implement the whole fuzzy inference method into silicon

Analyze analog, digital, and mixed-signal techniques

Reduce your design effort for fuzzy systems with CAD tools - learn the requirements they should meet and survey current environments.

Put it all together - see examples and case studies illustrating how all of this is used to solve particular problems related to control and neuro-fuzzy applications

Table of Contents

INTRODUCTION
Methods for Information Representation and Processing
Fuzzy Sets and Fuzzy Logic
A Brief History of Fuzzy Logic
Fuzzy Logic Application Domain
FUZZY SET THEORY
Fuzzy Sets
The Concept of Membership Function
Terminology for Fuzzy Sets
Operations with Fuzzy Sets
Fuzzy Relations
FUZZY INFERENCE SYSTEMS
Linguistic Variables
Fuzzy Rules
Approximate Reasoning Techniques
Rule-Based Inference Mechanisms
Defuzzification Methods
Types of Fuzzy Systems
Structure of a Fuzzy System
FUZZY SYSTEM DEVELOPMENT
Definition of a Fuzzy System
CAD Tools for Fuzzy Systems
The Xfuzzy Development Environment
FUZZY SYSTEM VERIFICATION
Learning Techniques for Fuzzy Systems
Learning on XFL-Based Systems
Simulation of Fuzzy Systems
Simulation of XFL-Based Systems
On-Line Verification of XFL-Based Systems
HARDWARE REALIZATION OF FUZZY SYSTEMS
Fuzzy System Implementations Depending on the Application
Fuzzy System Realizations with General-Purpose Processors
Fuzzy System Realizations with Dedicated Hardware
CONTINUOUS-TIME ANALOG TECHNIQUES FOR DESIGNING FUZZY INTEGRATED CIRCUITS
The First Analog Fuzzy Integrated Circuits
Fully Parallel Architectures
Fuzzification Stage
Rule Processing Stage
Output Stage
Design of a Current-Mode CMOS Prototype
DISCRETE-TIME ANALOG TECHNIQUES FOR DESIGNING FUZZY INTEGRATED CIRCUITS
Sequential Architectures
Fuzzification Stage
Rule Processing Stage
Output Stage
Timing and Inference Speed of Discrete-Time Singleton Fuzzy ICs
Design of an SC CMOS Prototype
DIGITAL TECHNIQUES FOR DESIGNING FUZZY INTEGRATED CIRCUITS
The First Digital Fuzzy Integrated Circuits
Architectures of Digital Fuzzy IntegratedCircuits
Fuzzification Stage
Rule Processing and Defuzzification Stages
Active Rule-Driven Architecture with Simplified Defuzzification Methods
FUZZY SYSTEM SYNTHESIS
Hardware Synthesis of Fuzzy Systems
Describing Fuzzy Systems with a Hardware Description Language: VHDL
Tools for Hardware Synthesis in Xfuzzy
A Design Methodology for Fuzzy Systems
FUZZY SYSTEMS AS CONTROLLERS
Conventional Control Systems
Fuzzy Control Systems
Application Example: Ball Suspended by an Air Flow
FUZZY SYSTEMS AS APPROXIMATORS
Approximation Capability of Fuzzy Systems
Applications using Off-Chip Learning
Application using On-Chip Learning