✍ Scribed by Akira Shimada
No coin nor oath required. For personal study only.
Disturbance Observer for Advanced Motion Control with MATLAB/Simulink
A fulsome and robust presentation of disturbance observers complete with MATLAB sample programs and simulation results
In Disturbance Observer for Advanced Motion Control with MATLAB/Simulink, distinguished electronics engineer Dr. Akira Shimada delivers a comprehensive exploration of the suppression of actual and unknown disturbances. In the book, you’ll find a systematic discussion of the basic theory and design methods of disturbance observers accompanied by instructive MATLAB and Simulink simulation examples.
Included appendices cover the mathematical background of classical, modern, and digital control and ground the reader’s understanding of the more advanced sections. The included material is ideal for students enrolled in courses in advanced motion control, mechatronics system control, electrical drives, motion control, robotics, and aeronautics.
In addition to topics like model predictive control, vibration systems, acceleration control, adaptive observers, and multi-rate sampling, readers will find:
Perfect for undergraduate and graduate students with existing knowledge of the fundamentals of control engineering who wish to learn how to design disturbance observers, Disturbance Observer for Advanced Motion Control with MATLAB/Simulink will also benefit professional engineers and researchers studying alternative control theories.
Cover
Title Page
Copyright
Contents
About the Author
Preface
About the Companion Website
Chapter 1 Introduction of Disturbance Observer
1.1 Types of Disturbance Observers
1.1.1 Introduction
1.1.2 Observer and Control System Design Concepts
1.2 Format of Example and Use of MATLAB
1.2.1 Format of the Example Problem
1.2.2 Using MATLAB/Simulink
1.3 How This Book Is Organized
1.3.1 The Structure of This Document
1.3.2 How to Read This Book
References
Chapter 2 Basics of Disturbance Observer
2.1 What Is Disturbance
2.2 How Disturbance Estimation Works
2.3 Disturbance Rejection and Acceleration Control System
2.3.1 Concept of Disturbance Rejection and Acceleration
2.3.2 Different Disturbance Observers Depending on How the Disturbance Is Captured
2.3.3 Basic Control System Design
2.4 Reaction Force Observer (RFOB)
2.4.1 Reaction Force Observer Design
2.4.2 Combined Use of DOB and RFOB
2.5 Internal Model and Two‐degrees‐of‐freedom Control
2.5.1 Internal Model Principle
2.5.2 Feedforward Control
2.5.3 Control System with Disturbance Observer and Feedforward
2.6 Effect of Observation Noise and Modeling Error
2.6.1 Effect of Observation Noise
2.6.2 Effect of Modeling Error
2.6.3 Effect of Viscous Friction
2.6.4 Effect of Varying Mass
2.7 Real System Modeling
2.7.1 DC Motor Torque Control Model
2.7.2 Without Current Feedback
2.7.3 Relationship Between the Cart Model and Rotary‐type Motor
2.8 Idea of Robust Control
References
Chapter 3 Stabilized Control and Coprime Factorization
3.1 Coprime Factorization and Derivation of Stabilizing Controller
3.1.1 Derivation of Parameters for Coprime Factorization
3.1.2 Stabilizing Controller and Free Parameters
3.1.3 Double Coprime Factorization Involving Q(s)
3.2 Relationship with Disturbance Observer
3.3 Coprime Factorization and Structure of Two‐degrees‐of‐freedom Control System
References
Chapter 4 Disturbance Observer in State Space
4.1 Identity Input Disturbance Observer
4.1.1 How to Design the Identity Input Disturbance Observer in Continuous System
4.1.2 Controllability and State Feedback
4.1.3 Continuous‐time Servo System with Identity Disturbance Observer
4.2 Identity Reaction Force Observer
4.3 Identity Output Disturbance Observer
4.4 Identity Higher Order Disturbance Observer Design
4.5 Minimal Order Disturbance Observer
4.6 Design of Periodic Disturbance Observer
4.7 Observability and Noninput/Output Disturbances
4.7.1 Mathematical Model of a DC Motor
4.7.2 DC Motor Observable Matrix and Rank
4.7.3 Observability of Disturbance Estimation
4.7.4 Noninput/Output Disturbance Observer and Control
References
Chapter 5 Digital Disturbance Observer Design
5.1 Identity Digital Disturbance Observer Design
5.2 Confirmation of Separation Theorem
5.3 Minimal Order Digital Disturbance Observer
5.4 Identity High‐order Digital Disturbance Observer
References
Chapter 6 Disturbance Observer of Vibrating Systems
6.1 Modeling of the Two‐inertia System
6.2 Vibration Suppression Control in Transfer Function Representation
6.3 Disturbance Observer and Stabilization for Two‐inertia Systems
6.3.1 Observer to Estimate Input Shaft Disturbance τd1
6.3.2 Observer to Estimate Output Shaft Disturbance τd2
6.4 Servo System with DOB for Two‐inertia Systems
6.4.1 Input Shaft Servo System Considering Input Shaft Disturbance τd1
6.4.2 Output Shaft Servo System Considering Output Shaft Disturbance τd2
References
Chapter 7 Communication Disturbance Observer
7.1 Smith Method Overview
7.2 Communication Disturbance Observer
7.3 Control with Communication DOB Under Disturbance
References
Chapter 8 Multirate Disturbance Observer
8.1 Multirate System Modeling
8.2 Multirate Disturbance Observer (Method 1)
8.2.1 Disturbance Observer Design (Method 1)
8.2.2 Controller Design Using Multirate Observer (Method 1)
8.3 Multirate Disturbance Observer (Method 2)
References
Chapter 9 Model Predictive Control with DOB
9.1 Model Predictive Control (MPC)
9.1.1 Overview of MPC
9.1.2 Formulation and Objective Function for the MPC Design
9.2 Constraint Descriptions
9.2.1 Treatment of Constraints on the Control Input û(k)
9.2.2 Constraints on the Control Variable ̂z(k)
9.2.3 Constraints on 𝚫û(k) Change in the Control Input
9.2.4 Constraints on the Control Inputs and Quantities
9.3 MPC System Design
9.4 Design of Disturbance Observer‐Merged MPC System
References
Chapter 10 Kalman Filter with Disturbance Estimation (KFD)
10.1 Design of Kalman Filter with Disturbance Estimation
10.2 Design of Stationary Kalman Filter with Disturbance Estimation (SKFD)
10.3 Design of Extended Kalman Filter with Disturbance Estimation (EKFD)
References
Chapter 11 Adaptive Disturbance Observer
11.1 Structure of an Adaptive Observer
11.2 Derivation of Observable Canonical System for Adaptive DOB
11.3 Creating State Variable Filter
11.4 Design of Kreisselmeier‐Type Adaptive Disturbance Observer
References
Chapter 12 Methods for Measuring and Estimating Velocities
12.1 Importance of Velocity Measurement
12.2 Velocity Measurement and Estimation Methods
12.2.1 Pseudo‐derivative
12.2.2 Counting and Timekeeping Methods
12.2.3 M/T Method
12.2.4 Synchronous Counting Method
12.2.5 Instantaneous Velocity Observer
References
Appendix A Mathematical Foundations and Control Theory
A.1 Mathematics
A.1.1 Definition and Calculus of Matrix Exponential Functions
A.1.2 Positive Definite Matrix
A.1.3 Matrix Rank
A.2 Basic Classical Control Theory
A.2.1 Poles and Zeros
A.2.2 PI Velocity Control
A.2.3 PID Position Control System
A.2.4 Final Value and Initial Value Theorems
A.3 Basic Modern Control Theory
A.3.1 State and Output Equations
A.3.2 Solution of the State Equation for the Continuous System
A.3.3 Equation of State to Transfer Function
A.3.4 Poles and Zeros of Continuous Systems
A.3.5 Controllability and Observability of Continuous Systems
A.3.6 Duality Theorem
A.3.7 State Feedback Control of Continuous Systems
A.3.8 Servo System Design
A.4 Doyle's Notation and Double Coprime Factorization
A.4.1 Doyle's Notation
A.4.2 Confirmation of Double Coprime Factorization
A.5 Foundations of Digital Control Theory
A.5.1 Digital Control and State and Output Equations
A.5.2 Poles and Zeros of Digital Systems
A.5.3 Reachability and Observability of Digital Systems
A.5.4 Digital State Feedback Control System Design
A.5.5 Digital Servo System Design
A.6 Representation and Meaning of Optimal Programming
A.6.1 What Is Optimal Programming?
A.6.2 fmincon Function
A.6.3 Example of a Drawing Program
References
Index
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