Миронович Владимир Анатольевич Генерация программ на основе функциональных блоков для промышленных киберфизических систем с использованием эволюционных алгоритмов

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Миронович Владимир Анатольевич Генерация программ на основе функциональных блоков для промышленных киберфизических систем с использованием эволюционных алгоритмов
ОГЛАВЛЕНИЕ ДИССЕРТАЦИИ
кандидат наук Миронович Владимир Анатольевич
Contents

Реферат

Synopsis

Introduction

Chapter 1 Background

1.1 Industrial Control systems

1.1.1 Industry

1.1.2 Industrial Cyber-physical Systems

1.1.3 Function Blocks: IEC 61131-3 and IEC

1.2 Model Checking

1.2.1 Basics

1.2.2 Liveness and Safety

1.2.3 Open-Loop and Closed-Loop Verification

1.3 Evolutionary Computation

1.3.1 Methods

1.3.2 Populations

1.3.3 Crossover

1.3.4 Population Diversity

1.3.5 Adaptation of Parameters

1.3.6 Restarts

1.3.7 Applications in Search-Based Software Engineering

1.3.8 Algorithms Used in This Thesis

1.4 Summary of Chapter

Chapter 2 Connection Generation Problem

2.1 Problem Statement

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2.1.1 Inter-device Generation of Connections

2.1.2 Intra-device Generation of Connections

2.2 Proposed Approach

2.2.1 Fitness Function

2.2.2 Individual Representation

2.2.3 Evolutionary Algorithms

2.3 Typical Problem Characteristics

2.4 Systems Used for Experimental Evaluations

2.4.1 Joystick Manipulator

2.4.2 Elevator Model

2.4.3 Pick-and-place manipulator

2.5 Summary of Chapter

Chapter 3 Fitness Function Design

3.1 General Considerations

3.1.1 Liveness and Safety

3.1.2 Simplified” Requirements

3.1.3 Preliminary Experiments

3.2 Fitness Function for the Considered Models

3.2.1 Fitness for the Joystick Model

3.2.2 Fitness for the Elevator Model

3.2.3 Fitness for the Pick-and-Place Manipulator Model

3.3 Summary of Chapter

Chapter 4 Evolutionary Algorithms for Connection Generation

4.1 Individual Representaion

4.1.1 Vector-based Individual Encoding

4.1.2 Vector-based Mutation Operators

4.1.3 Permutation-based Individual Encoding

4.1.4 Permutation-based Mutation Operators

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4.1.5 Experiments for the Permutation-based Representaion

4.2 Population Diversity

4.2.1 Fitness Landscape Analysis

4.2.2 Diversity Preservation Selection Operator

4.3 Algorithms for the Connection Generation Problem

4.3.1 Algorithms for the Inter-device Connection Genera-

tion Problem

4.3.2 Algorithms for the Intra-device Connection Genera-

tion Problem

4.4 Experiments: Basic Statistics

4.4.1 Joystick Model

4.4.2 Elevator, 9 variables

4.4.3 Elevator, 12 variables

4.4.4 Elevator, 15 variables

4.4.5 Pick-and-Place Manipulator

4.5 Introducing Restarts

4.6 Parameter Adaptation and Hyper-Heuristics

4.7 Summary of Chapter

Conclusion

References

List of Figures

List of Tables

Appendix A Copies of Author’s Publications