The block diagrams as engineering means for closed loop control, which have been established by classic control theory for decades, are replaced in the above mentioned book by networks, the signals are replaced by data. It corresponds to the „Industry 4.0“ and to the structure of today’s automatic control systems. Thereby a classic closed loop is treated not isolated from other elements of nowadays automation like bus communication and process logical control, and is completed in proposed book with new control elements, so called data stream managers (DSM). The proposed book treats the control theory systematically like it is done in classical books considering the new concept of data management. The theory is accompanied in the book with examples, exercises with solutions and MATLAB®-simulations.
Author(s): Serge Zacher
Publisher: Springer
Year: 2023
Language: English
Pages: 395
City: Cham
Preface
Contents
1 Closed Loop Control and Management
1.1 Introduction
1.1.1 The aim of this book
1.1.2 Content of this book
1.2 From Single Controller to Automation System
1.2.1 Historical Overview
1.2.2 Automation Levels
1.2.3 Automation Subsystems and Functions
1.3 Control
1.3.1 Closed Loop Control (CLC)
1.3.2 Open Loop Control
1.3.3 Examples of open and closed loop control
1.3.3.1 An antenna’s angular positions control
1.3.3.2 A water tank level control
1.3.4 Bus
1.4 Management
1.4.1 Management of Automation System
1.4.2 Management of CLC
1.4.3 Example of a CLC Life Cycle
1.5 Conceptions and Approaches, used in this book
1.5.1 Classical Control Theory
1.5.2 System-Approach
1.5.3 Bus-Approach
1.5.4 Symmetry and Antisymmetry
1.5.5 CLIMB & HOLD-modes
1.6 Summary: Data Stream Management
References
2 Basics of System Dynamics and Control Theory
2.1 Three Levels of Mathematical Descriptions
2.1.1 Introduction
2.1.2 Time Domain
2.1.3 Laplace-Domain
2.1.4 Frequency Domain
2.1.5 Summary
2.2 Plants
2.2.1 Proportional P-plants
2.2.2 Integral or I-plants
2.2.3 Derivative D-plants
2.3 Controllers
2.4 CLC Behavior
2.4.1 Example: Level Control
2.4.2 Stabilty
2.4.3 Retained Error
2.5 Simulation of CLC with MATLAB®
2.5.1 Scripts
2.5.2 Simulink-Model
References
3 Controller Tuning
3.1 Controller Tuning in Time Domain
3.1.1 Performance Criteria of Control
3.1.2 Settability of PTn Plants
3.1.3 Empirical Tuning Methods
3.1.4 Tuning of Controller Minimizing Integral Criterion
3.1.5 ITAE Criterion
3.2 Controller Tuning in Laplace Domain
3.2.1 Standard Controller
3.2.2 Open and Closed Loop
3.2.3 Model Based Compensating Controller
3.2.4 Tuning of Typical Simple Loops
3.2.5 Optimum Magnitude
3.2.6 Symmetrical Optimum
3.2.7 Pole Placing
3.2.8 Algebraic Stability Criterion of Hurwitz
3.3 Controller Tuning in Frequency Domain
3.3.1 Nyquist Stability Criterion
3.3.2 Controller Tuning with Bode-Plot
References
4 Bus-Approach
4.1 Definition of Virtual Bus
4.1.1 Curse of Dimensionality
4.1.2 Course of Dimensionality
4.2 Basics of Bus-Approach
4.2.1 Construction of Virtual Bus
4.2.2 Bus-Creator and Bus-Selector
4.2.3 Applications of Virtual Buses for SISO- and MIMO CLC
4.3 Bus-Approach for MIMO Control
4.3.1 Kinds of MIMO Plants
4.3.2 Kinds of Coupled MIMO Plants
4.3.3 Stability of Coupled MIMO Plants
4.3.4 Kinds of MIMO Control
4.3.5 Interaction Transfer Function and Coupling Gain
4.4 Stability of MIMO Control
4.4.1 Stability of MIMO Single-Loops Control
4.4.2 Stability of Separated MIMO Control
4.4.3 Stability Check with MATLAB®-Script
4.5 Summary
References
5 ASA: Antisystem Approach
5.1 What is ASA?
5.1.1 Definition of ASA
5.1.2 The Long Way to ASA
5.1.2.1 Duality
5.1.2.2 Group Theory
5.1.2.3 Symmetry
5.1.2.4 Antisymmetry
5.1.2.5 Compression of Variables
5.1.3 Examples of ASA Implementations
5.2 Basics of ASA
5.2.1 Introduction: ASA is Everywhere
5.2.2 Balance of Functions and Numbers
5.2.3 Balance of Algebraic Equations
5.3 ASA Application for Control
5.3.1 Balance Control
5.3.2 Compression and Extraction of Variables
5.3.3 MIMO Control
5.3.4 Multi-Stage MIMO Plants
5.3.5 ASA Control
References
6 BAD: Bode Aided Design
6.1 Introduction
6.1.1 Stability
6.1.2 Hurwitz Stability Criterion
6.2 Overview of Stability Criteria in Frequency Domain
6.2.1 Nyquist Stability Criterion
6.2.2 Mikhailov stability criterion
6.2.3 Leonhard Stability Criterion
6.3 Three Bode Plots
6.3.1 Conception
6.3.2 Two Bode Plots Method
6.3.3 Symmetry Operations With Controllers
6.3.4 Decomposition of mirrored controllers
6.3.5 3BP Method
6.3.6 Implementation of 3BP Method for Unstable Plants
6.4 BAD
6.4.1 Bode Plots of Mirrored Controllers
6.4.2 BAD of P controller
6.4.3 BAD of I controller
6.4.4 BAD of PID controller
6.5 Implementation of BAD
6.5.1 BAD upon one single frequency response
6.5.2 Bode plot upon single step response
References
7 Management of Identification
7.1 Introduction
7.1.1 Data Stream Management
7.1.2 DSM of this Chapter
7.2 DSM Ident
7.2.1 Structure
7.2.2 DSM Ident-1
7.2.3 DSM Ident 3
7.2.4 MATLAB® Script of DSM Ident 3
7.3 DSM Tuner
7.4 AFIC
7.4.1 Conception of Adaptive Filter for Identification and Control
7.4.2 Adaptive Filter: Theoretical Backgrounds
7.4.3 Identification of Plant
7.4.4 App DSM AFIC with MATLAB®
References
8 Management of Setpoint Behavior
8.1 Control and Management
8.1.1 Setpoint behavior and disturbance behavior
8.1.2 CLIMB and HOLD
8.1.3 Overview of DSM of this chapter
8.2 Dual control with reference model
8.2.1 SPFC
8.2.2 SFC
8.3 Override and Overset
8.3.1 DSM Override
8.3.2 DSM Overset
8.4 DSM with Neuro-Fuzzy elements
8.4.1 DSM Axon
8.4.2 FFF
References
9 Management of Disturbance Behavior
9.1 Introduction
9.1.1 Operating Modes of Closed Loop Control
9.1.2 Conceptions
9.2 DSM Terminator
9.2.1 Conception
9.2.2 Mathematical Backgrounds
9.2.3 DSM Terminator’s Application
9.2.4 DSM terminator with CLIMB & hOLD Controllers
9.3 Management and Control of LTV Plants
9.3.1 LTI and LTV
9.3.2 Gain Scheduling
9.3.3 DSM Plant Guard
9.3.4 Summary
Refereneces
10 Multivariable Control and Management
10.1 Introduction: What is MIMO Control?
10.1.1 Examples of MIMO Control
10.1.2 Kinds of MIMO Plants
10.1.3 Kinds of MIMO Closed Loop Control
10.2 Coupled MIMO Plants
10.2.1 Feed-Forward Plants
10.2.2 Interaction Transfer Function and Coupling Gain
10.2.3 Feed-back Plants
10.2.4 Conversion of FB-Plants into FF-Plants
10.2.5 Stability of Coupled MIMO Plants
10.3 Decoupled MIMO Control
10.3.1 Conception of Decoupling
10.3.2 Decoupled MIMO Control Loops
10.3.3 Stability Proof of FF-Plant with FB-Controller
10.3.4 Bus-Approach
10.3.5 Bus-Approach for Decoupled MIMO Control
10.3.6 MATLAB® Simulation of MIMO Control with Bus-Approach
10.4 Management of Decoupled MIMO Control
10.4.1 Data Stream Management
10.4.2 DSM Router
10.4.3 Implementation of DSM Router
10.4.4 Summary
References
11 Model-Based Control and Management
11.1 Classic Compensating Control
11.1.1 “Invalid” Plant
11.1.2 Compensating Controller
11.2 ASA Compensating Control
11.2.1 Antisystem Approach (ASA)
11.2.2 ASA Prefilter
11.2.3 ASA Controller
11.2.4 Shadow Plant
11.3 Date Stream Management of ASA Control
11.3.1 Data Stream by ASA Control
11.3.2 DSM Supervisor
11.3.3 DSM Bypass
11.3.4 ASA Predictor
11.3.5 DSM Turbo
11.3.6 Summary
References
