The University of Southampton
University of Southampton Institutional Repository

Intelligent Control: Aspects of Fuzzy Logic and Neural Networks

Harris, C.J., Moore, C.G. and Brown, M. (1993) Intelligent Control: Aspects of Fuzzy Logic and Neural Networks, vol. 6, World Scientific Press (Robotics and Automated Systems, 6).

Record type: Book


Index: 1. An Introduction to Intelligent Control 1.1 Preliminaries 1.2 Intelligent Control Requirements and Architectures 1.3 Approaches to Intelligent Control 1.4 Knowledge Based Systems 1.5 Fuzzy Logic 1.6 Fuzzy Logic in Control 1.7 Neurocontrollers 1.8 Higher Level Intelligent Controllers 1.9 Bibliographical Notes 2. Introductory Fuzzy Logic 2.1 Fuzzy Sets and Logic 2.2 Fuzzy Inference and Composition 2.3 Defuzzification 3. Fuzzy Logic Controller Structure and Design 3.1 Introduction 3.2 Applications of Fuzzy Set Theory 3.3 Fuzzy Logic Controller Structural Issues 3.4 Design Requirements of Fuzzy Logic Controllers 4. The Static Fuzzy Logic Controller 4.1 Introduction 4.2 Controller Design by Verbalisation or Expert Interrogation 4.3 The Fuzzy PID Controller 4.4 Parametrically Determined Fuzzy PID Controllers 4.5 Linguistic Rule Inversion Fuzzy Logic Controllers 4.6 Cluster Based Fuzzy Logic Controllers 5. Self-Organising Fuzzy Logic Control 5.1 Introduction 5.2 Control Rule Base SOFLICs 5.3 Rule Based SOFLIC Applications 5.4 Systematic Design of Control Rule Based SOFLIC 6. Indirect Self-Organising Fuzzy Logic Controllers 6.1 Introduction 6.2 Self-Organising Fuzzy Models and Predictors 6.3 Relation Causality Inversion 6.4 Controller Design 6.5 Adaptive Fuzzy Controller 6.6 A Simulation Example of Indirect Adaptive Fuzzy Logic Control 6.7 Nested and Hybrid Fuzzy Controllers 7. Case Studies of Indirect Adaptive Fuzzy Control 7.1 Regulation of a Ship's Heading 7.2 Track Control of a City Bus 7.3 Autonomous Road Vehicle Control and Guidance 7.4 Observations on Indirect Fuzzy Adaptive Control 8. Neural Network Approximation Capability for Control and Modelling 8.1 Introduction 8.2 Approximation Capability of Artificial Neural Networks 8.3 Multilayer Perceptrons in Neurocontrol 8.4 Radial Basis Functions in Modelling and Control 9. The B-spline Neural Network and Fuzzy Logic 9.1 Introduction 9.2 Polynomial Basis Functions 9.3 B-splines for Guidance 9.4 Multivariate Basis Functions 9.5 Weighted Adaptation 9.6 B-spline Neural Net Nonlinear Time Series Predictors and Modelling 9.7 A Comparison between Fuzzy Logic and Single Layer Associative Memory Neural Networks 9.8 Conclusions Appendix: Mathematical Prerequisites A.1 Metric Spaces A.2 Normed Metric Spaces A.3 Algebras A.4 Approximation in Normed Spaces Contents

Full text not available from this repository.

More information

Published date: 1993
Organisations: Southampton Wireless Group


Local EPrints ID: 250227
PURE UUID: e362dedc-8e34-4e7b-b8a9-5bec8c426a36

Catalogue record

Date deposited: 04 May 1999
Last modified: 18 Jul 2017 10:43

Export record


Author: C.J. Harris
Author: C.G. Moore
Author: M. Brown

University divisions

Download statistics

Downloads from ePrints over the past year. Other digital versions may also be available to download e.g. from the publisher's website.

View more statistics

Atom RSS 1.0 RSS 2.0

Contact ePrints Soton:

ePrints Soton supports OAI 2.0 with a base URL of

This repository has been built using EPrints software, developed at the University of Southampton, but available to everyone to use.

We use cookies to ensure that we give you the best experience on our website. If you continue without changing your settings, we will assume that you are happy to receive cookies on the University of Southampton website.