Intelligent Control Systems: An Introduction with Examples

Intelligent Control Systems: An Introduction with Examples




Intelligent control is a rapidly developing, complex and challenging field with great practical importance and potential. Because of the rapidly developing and interdisciplinary nature of the subject, there are only a few edited volumes consisting of research papers on intelligent control systems but little is known and published about the fundamentals and the general know-how in designing, implementing and operating intelligent control systems.
Intelligent control system emerged from artificial intelligence and computer controlled systems as an interdisciplinary field. Therefore the book summarizes the fundamentals of knowledge representation, reasoning, expert systems and real-time control systems and then discusses the design, implementation verification and operation of real-time expert systems using G2 as an example. Special tools and techniques applied in intelligent control are also described including qualitative modelling, Petri nets and fuzzy controllers. The material is illlustrated with simple examples taken from the field of intelligent process control.
Audience: The book is suitable for advanced undergraduate students and graduate engineering students. In addition, practicing engineers will find it appropriate for self-study.



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Published 01 January 1983
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EAN13 0306480816
License: All rights reserved
Language English

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Acknowledgments Preface 1.GETTING STARTED 1.Intelligent control: what does it mean? 2.Components of intelligent control systems 2.1Software elements 2.2Users 3.the bookThe structure and use of 3.1The structure of the material 3.2Prerequisites and potential readers 3.3Course variants 2. KNOWLEDGE REPRESENTATION 1.Data and knowledge 1.1Data representation and data items in traditional databases 1.2Data representation and data items in relational databases 2.Rules 2.1Logical operations 2.2Syntax and semantics of rules 2.3Datalog rule sets 2.3.1 The dependence graph of datalog rule sets 3.Objects 4.Frames 5.Semantic nets 3. REASONING AND SEARCH IN RULEBASED SYSTEMS 1.Solving problems by reasoning 1.1The structure of the knowledge base 1.2The reasoning algorithm 1.3Conflict resolution vii
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1.4 Explanation of the reasoning Forward reasoning 2.1forward reasoningThe method of 2.2A simple case study of forward reasoning Backward reasoning 3.1Solving problems by reduction 3.2backward reasoningThe method of 3.3A simple case study of backward reasoning Bidirectional reasoning Search methods 5.1The general search algorithm 5.2Depthfirst search 5.3Breadthfirst search 5.4Hill climbing search 5.5A* search
4. VERIFICATION AND VALIDATION OF RULEBASES 1.Contradiction freeness 1.1The notion of contradiction freeness 1.2Testing contradiction freeness 1.3The search problem of contradiction freeness 2.Completeness 2.1completenessThe notion of 2.2Testing completeness 2.3The search problem of completeness 3.Further problems 3.1freeness and completenessJoint contradiction 3.2Contradiction freeness and completeness in other types of knowledge bases 4.Decomposition of knowledge bases 4.1Strict decomposition 4.2Heuristic decomposition 5.TOOLS FOR REPRESENTATION AND REASONING 1.The Lisp programming language 1.1The fundamental data types in Lisp 1.2Expressions and their evaluation 1.3Some useful Lisp primitives 1.3.1 The QUOTE primitive 1.3.2 Primitives manipulate on lists 1.3.3 Assignment primitives 1.3.4 Arithmetic primitives 1.3.5 Predicates 1.3.6 Conditional primitives 1.3.7 Procedure definition 1.4Some simple examples in Lisp 1.4.1 Logical functions 1.4.2Calculating sums
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1.4.3 Polynomial value 2.The Prolog programming language 2.1The elements of Prolog programs 2.1.1Facts 2.1.2Rules 2.1.3 Questions 2.1.4The Prolog program 2.1.5 The declarative and procedural views of a Prolog program 2.1.6More about lists 2.2The execution of Prolog programs 2.2.1How questions work 2.2.2Unification 2.2.3Backtracking 2.2.4Tracing Prolog execution 2.2.5The search strategy 2.2.6Recursion 2.3Builtin predicates 2.3.1 Inputoutput predicates 2.3.2Dynamic database handling predicates 2.3.3Arithmetic predicates 2.3.4Expressionhandling predicates 2.3.5Control predicates 2.4Some simple examples in Prolog 2.4.1Logical functions 2.4.2Calculation of sums 2.4.3Path finding in a graph 3.Expert system shells 3.1an expert system shellComponents of 3.2Basic functions and services in an expert system shell 6.REALTIME EXPERT SYSTEMS 1.The architecture of realtime expert systems 1.1The realtime subsystem 1.2The intelligent subsystem 2.Synchronization and communication between realtime and intelligent subsystems 2.1Synchronization and communication primitives 2.2Priority handling and timeout 3.Data exchange between the realtime and the intelligent subsystems 3.1Loose data exchange 3.2The blackboard architecture 4.realtime expert systemsSoftware engineering of 4.1realtime expert systemsThe software lifecycle of 4.2Special steps and tools 7. QUALITATIVE REASONING
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1.Sign and interval calculus 1.1Sign algebra 1.2Interval algebras 2.Qualitative simulation 2.1Constraint type qualitative differential equations 2.2The solution of QDEs: the qualitative simulation algorithm 2.2.1Initial data for the simulation 2.2.2Steps of the simulation algorithm 2.2.3Simulation results 3.Qualitative physics 3.1Confluences 3.2The use of confluences 4.Signed directed graph (SDG) models 4.1The structure graph of statespace models 4.2The use of SDG models 8.PETRI NETS 1.Petri netsThe Notion of 1.1The basic components of Petri nets 1.1.1 Introductory examples 1.1.2 The formal definition of Petri nets 1.2The firing of transitions 1.3Special cases and extensions 1.3.1 Source and sink transitions 1.3.2Selfloop 1.3.3 Capacity of places 1.3.4 Parallelism 1.3.5 Inhibitor arcs 1.3.6Decomposition of Petri nets 1.3.7 Time in Petri nets 1.4The statespace of Petri nets 1.5The use of Petri nets for intelligent control 2.Petri netsThe analysis of 2.1Analysis Problems for Petri Nets 2.1.1 Safeness and Boundedness 2.1.2Conservation 2.1.3Liveness 2.1.4Reachability and Coverability 2.1.5 Structural properties 2.2Analysis techniques 2.2.1The reachability tree 2.2.2Analysis with matrix equations 9.FUZZY CONTROL SYSTEMS 1.Introduction 1.1fuzzinessThe notion of 1.2Fuzzy controllers 2.Fuzzy sets
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2.1Definition of fuzzy sets192 2.2Operations on fuzzy sets200 2.2.1Primitive fuzzy set operations201 2.2.2Linguistic modifiers205 2.3Inference on fuzzy sets208 2.3.1 Relation between fuzzy sets209 2.3.2Implication between fuzzy sets211 2.3.3Inference on fuzzy sets214 3.Rulebased fuzzy controllers215 3.1Design of fuzzy controllers216 3.1.1 The input and output signals216 3.1.2 The selection of universes and membership functions217 3.1.3 The rulebase219 3.1.4 The rulebase analysis220 3.2The operation of fuzzy controllers223 3.2.1The preproccessing unit223 3.2.2The inference engine223 3.2.3The postprocessing unit225 10.G2: AN EXAMPLE OF A REALTIME EXPERT SYSTEM227 1.Knowledge representation in G2228 2.the knowledge baseThe organization of 230 2.1Objects and object definitions231 2.2Workspaces232 2.3Variables and parameters233 2.4Connections and relations234 2.5Rules235 2.6Procedures237 2.7Functions238 3.Reasoning and simulation in G2239 3.1The realtime inference engine239 3.2The G2 simulator240 4.Tools for developing and debugging knowledge bases241 4.1The developers’ interface241 4.1.1 The graphic representation241 4.1.2G2 grammar242 4.1.3 The interactive text editor242 4.1.4 The interactive icon editor243 4.1.5 Knowledge base handling tools244 4.1.6Documenting in the knowledge base245 4.1.7 Tracing and debugging facilities246 4.1.8 The access control facility247 4.2The enduser interface247 4.2.1Displays247 4.2.2Enduser controls248 4.2.3Messages, message board and logbook249 4.3External interface250
Appendices251 A–A BRIEF OVERVIEW OF COMPUTER251 CONTROLLED SYSTEMS 1.Basic notions in systems and control theory251 1.1Signals and signal spaces252 1.2Systems252 2.Statespace models of linear and nonlinear systems253 2.1Statespace models of LTI systems254 2.2Statespace models of nonlinear systems254 2.3Controllability255 2.4Observability256 2.5Stability257 3.Common functions of a computer controlled system258 3.1Primary data processing258 3.2Process monitoring functions260 3.3Process control functions260 3.4Functional design requirements262 4.Realtime software systems262 4.1Characteristics of realtime software systems262 4.2Elements of realtime software systems264 4.3Tasks in a realtime system264 5.Software elements of computer controlled systems268 5.1computer controlledCharacteristic data structures of systems268 5.1.1 Raw measured data and measured data files269 5.1.2Primary processing data file270 5.1.3 Events data file270 5.1.4 Actuator data file271 5.2Typical tasks of computer controlled systems272 5.2.1Measurement device handling272 5 . 2 . 2Primary and secondary processing272 5.2.3Event handling272 5 . 2 . 4actuator handlingController(s) and 273 B– THE COFFEE MACHINE275 1.System description275 2.Dynamic model equations277 2.1Differential (balance) equations278 2.2System variables279 References281 Index289 About the Authors301