Modeling, Diagnostics and Process Control (eBook)

Preface 5
Contents 8
Introduction 14
Control System Structures 14
Trends in the Development of Modern Automatic Control Systems 18
New Functions of Advanced Automatic Control Systems 20
Introduction to the DiaSter System 27
Introduction 27
System Structure and Tasks 27
Main Uses of the System 27
System Functionality 29
System Structure 37
Software Platform 39
Information Model and the System Configuration 41
Central Archival Database and User Databases 44
Data Exchange 49
Modeling Module 51
On-line Calculation Module 56
Visualization Module 60
Process Modeling 66
Introduction 66
Analytical Models and Modeling 68
Basic Relations for the Description of Balance Dependencies for Modeled Physical Processes 69
Integration Methods and Integration Step Selection for Simulation 73
Pneumatic Cylinder Controlled by a Servo-Valve: A Balance Model of the System 75
Pneumatic Cylinder Controlled by a Servo-Valve: A Block Model of the System 81
Linear Models: Local Approximation of Dynamic Properties 83
Dynamic Model Linearization 83
Pneumatic Cylinder Controlled by a Servo-Valve: A Linear Model of the System 85
Pneumatic Cylinder Controlled by a Servo-Valve: An Optimized Linear Model of the System 89
Parametric Models 93
Discrete Linear Parametric Models 94
Identification of the Coefficients of Parametric Models 97
Pneumatic Cylinder Controlled by a Servo-Valve: A Parametric Linear Model of the System 100
Fuzzy Parametric Models 103
Fuzzy Parametric TSK Models 103
Estimation of Fuzzy TSK Model Coefficients 105
Pneumatic Cylinder Controlled by a Servo-Valve: A TSK Fuzzy Model 107
Neural Models 110
Neural Networks with External Dynamics 111
Recurrent Networks 112
State Space Neural Networks 114
Locally Recurrent Networks 115
GMDH Neural Networks 122
Implementation of Neural Models in the DiaSter System 129
Knowledge Discovery in Databases 130
Introduction 130
Selection of Input Variables of Models 132
Correlation-Based Feature Selection 133
Measures Based on Correlation 134
Searching through the Feature Space 135
Discovery of Qualitative Dependencies 136
Discovery of Quantitative Dependencies 139
Support Vector Machines 139
Methods Involving Case-Based Reasoning 145
Conclusion 163
Diagnostic Methods 164
Introduction 164
Specificity of the Diagnostics of Industrial Processes 165
Fault Detection Methods 166
Robust Fault Diagnosis 171
Robust Neural Model: The Passive Approach 172
Fuzzy Adaptive Threshold: The Passive Approach 175
Robust Dynamic Model: The Active Approach 177
Robust Model Design Examples 180
Implementation of Neural Models in the DiaSter System 186
Process Fault Isolation with the Use of Fuzzy Logic 190
Forms of Diagnostic Relation Notation 190
Reasoning Algorithm for Single and Multiple Faults 195
Algorithms of Reasoning in a Hierarchical Structure 206
Application of Belief Networks in Technical Diagnostics 217
Introduction 218
Belief-Network-Based Diagnostic Model 221
Input Data Images 224
Additional Variables and Opportunities for Their Adjustment 230
Belief Networks 233
Model Identification and Tuning 240
Implementation in the DiaSter Environment 242
Supervisory Control and Optimization 243
Predictive Control and Process Set-Point Optimization 244
Principle of Model-Based Predictive Control 245
Dynamic Matrix Control Algorithm 250
Generalized Predictive Control Algorithm 257
Non-linear Predictive Control 260
Optimization of Set-Points 266
Examples 269
Self-tuning and Adaptation of Control Loops 277
Step Response Method 277
Relay Self-tuning 286
Loop Adaptation 292
Function Blocks 301
Application of the DiaSter System 304
Introduction 304
System of Automatic Control and Diagnostics 305
Process Information Model in the DiaSter Platform 307
Applications of the DiaSter System Packages 311
Process Simulator 312
Self-tuning: Selection of PID Settings 317
Reconstructing Process Variables with TSK Models 322
Process Modeling with Neural Networks 328
Incipient Fault Tracking 335
On-Line Diagnostics with Fuzzy Reasoning 337
Belief Networks in a Diagnostic System 347
Knowledge Discovery in Databases 358
Model Predictive Control with Constraints and Faulty Conditions 371
References 377
Index 389