AN INTRODUCTION TO INTELLIGENT AND AUTONOMOUS CONTROL

PANOS J. ANTSAKLIS AND KEVIN M. PASSINO, EDS.

KLUWER ACADEMIC PUBLISHERS, NORWELL MA, 1993.

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Back cover of the book:

The area of Intelligent Control is a fusion of a number of research areas
in engineering, computer science, and mathematics which has evolved from
conventional control to enhance the existing nonlinear, optimal, adaptive,
and stochastic control methods.  Intelligent control techniques are
currently being utilized for closed-loop feedback control in space-based
applications, manufacturing systems, robotic systems, avionic systems,
among others, to enhance system performance, reliability, and efficiency. 
Overall, the primary objective of intelligent control is to enhance the
performance of the system to the extent that it achieves some level of
autonomous operation.

An Introduction to Intelligent and Autonomous Control provides an
introduction to, and survey of the vital and emerging area of intelligent
control by leading researchers in the area.  The fundamental theory,
architectures, and perspectives on intelligent control are presented. 
Approaches to intelligent control, including expert control, planning
systems, fuzzy control, neural control, and learning control are studied in
detail.  Applications are introduced via robotic systems, avionic systems,
and failure diagnosis for process operations.

An Introduction to Intelligent and Autonomous Control is a reference for
professionals and academic researchers and may be used as the foundation
for graduate level courses on Intelligent and Autonomous Control.

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Table of Contents:

Preface: George N. Saridis

Overview: Panos J. Antsaklis and Kevin M. Passino 


Part I: Theory and Architectures

Chapter 1: 	Introduction to Intelligent Control Systems
		with High Degrees of Autonomy

				Panos J. Antsaklis and Kevin M. Passino

Chapter 2: 	A Reference Model Architecture for
		Intelligent Systems Design

				James S. Albus

Chapter 3: 	Model-Based Architecture Concepts for 
		Autonomous Systems Design and Simulation

				Bernard P. Zeigler and Sungdo Chi

Chapter 4: 	Design of Structure-Based Hierarchies for 
		Distributed Intelligent Control

				Levent Acar and Umit Ozguner

Chapter 5: 	Modeling and Design of Distributed 
		Intelligence Systems

				Alexander H. Levis

Chapter 6: 	Nested Hierarchical Control

				Alex Meystel 


Part II: Design Approaches and Techniques

Chapter 7: 	Expert Control

				Karl J. Astrom and Karl-Erik Arzen

Chapter 8: 	Modeling and Analysis of Artificially 
		Intelligent Planning Systems

				Kevin M. Passino and Panos J. Antsaklis

Chapter 9: 	Fuzzy and Neural Control
 
				Hamid R. Berenji

Chapter 10:	Learning Control Systems

				Jay A. Farrell and Walter Baker

Chapter 11:	Learning Control: Methods, Needs and Architectures

				Mieczyslaw M. Kokar

Chapter 12:	Learning in Control

				Edward Grant

Part III: Applications

Chapter 13:	Intelligent Robot Prehension

				Thang N. Nguyen and Harry Stephanou

Chapter 14:	Modeling of Multi Sensory Robotic Systems
		with Failure Diagnostic Capabilities

				Kimon P. Valavanis and Guna Seetharaman

Chapter 15:	AUTOCREW: A Paradigm for Intelligent Flight Control

				Brenda L. Belkin and Robert F. Stengel

Chapter 16:	A Framework for Knowledge-Based Diagnosis 
		in Process Operations

				P.R. Prasad and James F. Davis

Index