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- Herausgeber: John Wiley & Sons
- Kategorie: Wissenschaft und neue Technologien
- Serie: Wiley-IEEE Press Book Series on Control Systems Theory and Applications
- Sprache: Englisch
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: * A thorough introduction to the various types of disturbance observers and the fundamentals of disturbance observers, including disturbance estimation and disturbance rejection * Comprehensive explorations of stabilized control and coprime factorization, including the derivation of stabilizing controllers * Practical discussions of disturbance observers in state space, including identity input disturbance observers and identity reaction force observers * Fulsome treatments of the mathematical foundations of control theory, methods??for measuring and estimating velocities, and the disturbance estimation Kalman filter 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.
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Table of Contents
Cover
Title Page
Copyright
About the Author
Preface
References
About the Companion Website
1 Introduction of Disturbance Observer
1.1 Types of Disturbance Observers
1.2 Format of Example and Use of MATLAB
1.3 How This Book Is Organized
References
Notes
2 Basics of Disturbance Observer
2.1 What Is Disturbance
2.2 How Disturbance Estimation Works
2.3 Disturbance Rejection and Acceleration Control System
2.4 Reaction Force Observer (RFOB)
2.5 Internal Model and Two‐degrees‐of‐freedom Control
2.6 Effect of Observation Noise and Modeling Error
2.7 Real System Modeling
2.8 Idea of Robust Control
References
Notes
3 Stabilized Control and Coprime Factorization
3.1 Coprime Factorization and Derivation of Stabilizing Controller
3.2 Relationship with Disturbance Observer
3.3 Coprime Factorization and Structure of Two‐degrees‐of‐freedom Control System
References
Notes
4 Disturbance Observer in State Space
4.1 Identity Input 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
References
Notes
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
Notes
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
6.4 Servo System with DOB for Two‐inertia Systems
References
Notes
7 Communication Disturbance Observer
7.1 Smith Method Overview
7.2 Communication Disturbance Observer
7.3 Control with Communication DOB Under Disturbance
References
Notes
8 Multirate Disturbance Observer
8.1 Multirate System Modeling
8.2 Multirate Disturbance Observer (Method 1)
8.3 Multirate Disturbance Observer (Method 2)
References
Notes
9 Model Predictive Control with DOB
9.1 Model Predictive Control (MPC)
9.2 Constraint Descriptions
9.3 MPC System Design
9.4 Design of Disturbance Observer‐Merged MPC System
References
Notes
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
Notes
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
Notes
12 Methods for Measuring and Estimating Velocities
12.1 Importance of Velocity Measurement
12.2 Velocity Measurement and Estimation Methods
References
Notes
Appendix A: Mathematical Foundations and Control Theory
A.1 Mathematics
A.2 Basic Classical Control Theory
A.3 Basic Modern Control Theory
A.4 Doyle's Notation and Double Coprime Factorization
A.5 Foundations of Digital Control Theory
A.6 Representation and Meaning of Optimal Programming
References
Notes
Index
End User License Agreement
List of Tables
Chapter 1
Table 1.1 Types of disturbance observer design.
Chapter 4
Table 4.1 Observability comparison 1.
Table 4.2 Observability comparison 2.
Chapter 6
Table 6.1 Kinds of outputs and disturbances
List of Illustrations
Chapter 1
Figure 1.1 Basic structure of the control system based on acceleration contr...
Figure 1.2 Structural diagram of this book.
Chapter 2
Figure 2.1 Images of a linear motion mechatronics system (cart model).
Figure 2.2 Images of a linear motion mechatronics system (cart model) under ...
Figure 2.3 Basic principle and representation format of disturbance observer...
Figure 2.4 Principle of disturbance rejection using disturbance estimates. (...
Figure 2.5 Board diagram for (example with s).
Figure 2.6 Apparent acceleration control system.
Figure 2.7 How to handle disturbances. (a) Viscous friction is included in p...
Figure 2.8 Disturbance cancel using disturbance estimates for a system with ...
Figure 2.9 Block diagram of PI velocity control system with DOB. (a) Speed c...
Figure 2.10 Simulink model of basic PI velocity control system with DOB.
Figure 2.11 Simulation of a PI velocity control system (switch on/off corres...
Figure 2.12 Basic principle of reaction force observer. (a) Basic reaction f...
Figure 2.13 Block diagram of the combined DOB/RFOB reaction force control sy...
Figure 2.14 Simulink model example of Reaction force control with RFOB.
Figure 2.15 Simulation result of reaction force control with RFOB. (a) React...
Figure 2.16 Two kinds of environment models. (a) Voigt model and (b) Maxwell...
Figure 2.17 Basic structure of control system with DOB.
Figure 2.18 Equivalent transformation for control system with DOB. (a) Equiv...
Figure 2.19 Equivalent transformation system with positive feedback of distu...
Figure 2.20 Positive feedback of first‐order disturbance estimate. (a) Distu...
Figure 2.21 Structure of feed‐forward control system. (a) Example of a feedf...
Figure 2.22 DOB and feedforward combined control system.
Figure 2.23 Simulation of PI velocity control system (with noise). (a‐1) Dis...
Figure 2.24 PI control system with viscous friction as disturbance.
Figure 2.25 Effect of changing the viscous friction on the characteristics. ...
Figure 2.26 PI control system with viscous friction as the disturbance.
Figure 2.27 Effect of changing the mass on the characteristics. (a‐1) Bode d...
Figure 2.28 Block diagram of the DC motor torque control system.
Figure 2.29 DC motor torque control system with voltage control.
Figure 2.30 Block diagram of the cart model with DC motor.
Chapter 3
Figure 3.1 Block diagram of the combined observer control system to illustra...
Figure 3.2 Block diagram of stabilization controller . (a) Block diagram of...
Figure 3.3 Block diagram of a closed loop system.
Figure 3.4 Block diagram of a stabilized control system with free parameters...
Figure 3.5 Block diagram of a two‐degrees‐of‐freedom control system includin...
Figure 3.6 Example of a Simulink model of a two‐degrees‐of‐freedom control s...
Figure 3.7 Simulation results for a two‐degrees‐of‐freedom control system. (...
Figure 3.8 Block diagram of a two‐degrees‐of‐freedom control system includin...
Chapter 4
Figure 4.1 Block diagram of the identity disturbance observer.
Figure 4.2 Identity disturbance observer with and represented separately...
Figure 4.3 Block diagram of identity noninput/output disturbance observer.
Figure 4.4 Simulink model of velocity observation input disturbance observer...
Figure 4.5 Simulated waveform of a velocity observation input disturbance ob...
Figure 4.6 Simulink model of control system with input disturbance observer ...
Figure 4.7 Simulation results of the control system with input disturbance o...
Figure 4.8 Simulation of the control system with identity observer in positi...
Figure 4.9 Simulink model of identity DOB‐combined control system with posit...
Figure 4.10 Simulation of a servo system with input end DOB with position ob...
Figure 4.11 Simulink model of identity reaction force observer with position...
Figure 4.12 Simulation results of identity reaction force observer with posi...
Figure 4.13 Example of a Simulink model of an output disturbance observer.
Figure 4.14 Simulation example of output disturbance observer. (a) Disturban...
Figure 4.15 Simulink model of high‐order DOB.
Figure 4.16 Disturbance and estimated value for ramped (first‐order) disturb...
Figure 4.17 Block diagram of minimal order observer.
Figure 4.18 Minimal order disturbance observer with velocity observation.
Figure 4.19 Equivalent disturbance observer with velocity observation. (a) D...
Figure 4.20 Position‐observing disturbance observer.
Figure 4.21 Equivalent disturbance observer with position observation. (a) D...
Figure 4.22 Equivalent disturbance observer conversion result with position ...
Figure 4.23 Simulink model of DOB for ramp (first‐order) disturbance.
Figure 4.24 Waveform of ramp (first‐order) disturbance observer. (a) Estimat...
Figure 4.25 Simulink model of periodic disturbance observer.
Figure 4.26 Simulation example of periodic disturbance observer. (a‐1) Distu...
Figure 4.27 Image of a DC motor with a torsion spring.
Figure 4.28 Transfer function block diagram of DC motor.
Figure 4.29 Simulink model of DOB for DC motors with large inductance.
Figure 4.30 Simulation results of DOB for DC motors with large inductance. (...
Chapter 5
Figure 5.1 Block diagram of digital
disturbance observer
(
DOB
).
Figure 5.2 Block diagram of a digital DOB (individual element representation...
Figure 5.3 Block diagram of digital identity DOB with velocity observation....
Figure 5.4 Simulink model of digital identity DOB with velocity observation....
Figure 5.5 Simulation result digital identity DOB with velocity observation....
Figure 5.6 Block diagram of identity digital disturbance observer with posit...
Figure 5.7 Block diagram of minimal order digital observer.
Figure 5.8 Minimal order digital disturbance observer in velocity observatio...
Figure 5.9 Transformation of minimal order digital DOB for velocity observat...
Figure 5.10 Comparison of and . (a) Simulink model and (b) wave form.
Figure 5.11 Simulink model of minimal order digital DOB with velocity observ...
Figure 5.12 Simulation result of minimal order digital DOB with velocity obs...
Figure 5.13 Minimal order digital disturbance observer in position observati...
Figure 5.14 Simulink model of minimal order digital DOB in position observat...
Figure 5.15 Simulation results for a minimal order digital DOB in position o...
Figure 5.16 Simulink model of digital PI velocity control system.
Figure 5.17 Simulation of digital PI velocity control system. (a‐1) Disturba...
Figure 5.18 Simulink model of higher order digital DOB.
Figure 5.19 Simulation example of higher order digital DOB. (a) Second‐order...
Chapter 6
Figure 6.1 Two‐inertia system.
Figure 6.2 Block diagram of the two‐inertia system transfer function. (a) Bl...
Figure 6.3 Bode diagram example of two inertia system. (a) Represents the ga...
Figure 6.4 Simulink model of velocity PI control system using simple
disturb
...
Figure 6.5 Simulation results of velocity PI control using simple DOB for a ...
Figure 6.6 Output shaft gain diagram of simple speed control system with DOB...
Figure 6.7 Simulation results of a velocity PI control system ( seconds) us...
Figure 6.8 Example of a Simulink model of a control system for estimating in...
Figure 6.9 Simulation results for a two‐inertia system with input shaft dist...
Figure 6.10 Simulink model of control system to estimate output shaft distur...
Figure 6.11 Simulation results with output shaft disturbance in a two‐inerti...
Figure 6.12 Simulink model of input shaft servo system considering input sha...
Figure 6.13 Simulation of input shaft servo system considering input shaft d...
Figure 6.14 Simulink model of output shaft servo system considering output s...
Figure 6.15 Simulation of output shaft servo system. (a) Output shaft distur...
Chapter 7
Figure 7.1 Basic block diagram of the Smith method.
Figure 7.2 Block diagram of the Smith method incorporating a communication d...
Figure 7.3 Simulink model of control system with Smith method.
Figure 7.4 Simulink model of control system incorporating CDOB.
Figure 7.5 Comparison of control system with Smith method and control system...
Figure 7.6 Configuration of control system with CDOB under disturbances.
Figure 7.7 Simulink model of control system with CDOB in the presence of dis...
Figure 7.8 Simulation results with time delay and disturbance. (a) Position ...
Chapter 8
Figure 8.1 Conceptual diagram of state variables and inputs in multirate.
Figure 8.2 Conceptual diagram of input conversion in multirate control.
Figure 8.3 Simulink model of control system with multirate DOB (Method 1). (...
Figure 8.4 Simulation results for control system with multirate
disturbance
...
Figure 8.5 Simulink model of control system with multirate DOB (Method 2).
Figure 8.6 Simulation results of multirate DOB‐combined control system (Meth...
Chapter 9
Figure 9.1 Model predictive control system. (a) Block diagram of model predi...
Figure 9.2 Simulink model example of MPC.
Figure 9.3 An example of MPC simulation. (a) Control input and (b) positio...
Figure 9.4 Simulink model of disturbance observer‐merged MPC.
Figure 9.5 Simulation example of DOB‐merged MPC. (a) Disturbance and estimat...
Chapter 10
Figure 10.1 Block diagram of the disturbance estimation Kalman filter.
Figure 10.2 Simulink model of Kalman filter with disturbance estimation with...
Figure 10.3 Simulation results of disturbance estimation Kalman filter with ...
Figure 10.4 Simulink model of a position servo system with a Kalman filter f...
Figure 10.5 Simulink model of position servo system with minimal order digit...
Figure 10.6 Simulation results of Kalman filter with disturbance estimation ...
Figure 10.7 Simulink model of a position servo system with a disturbance obs...
Figure 10.8 Simulation results of a position servo system with disturbance o...
Figure 10.9 Simulink model of a position servo system with disturbance estim...
Figure 10.10 Comparison of the structures of disturbance estimation steady‐s...
Figure 10.11 Image of one‐link manipulator.
Figure 10.12 Example Simulink model of an EKF that also estimates disturbanc...
Figure 10.13 Simulation example of control system with disturbance estimatio...
Chapter 11
Figure 11.1 Basic structure of the adaptive observer.
Figure 11.2 Nonminimal realization model of controlled plant with disturbanc...
Figure 11.3 Simulink model of nonminimal realization model.
Figure 11.4 Comparison of positional waveforms for nonminimal realization mo...
Figure 11.5 Simulink model of an adaptive disturbance observer control syste...
Figure 11.6 Subsystems for adaptive disturbance observer. (a) Block diagram ...
Figure 11.7 Disturbance estimation for adaptive DOB combined control system....
Figure 11.8 Simulation results of a control system with an adaptive disturba...
Chapter 12
Figure 12.1 Noise propagation in angle control systems.
Figure 12.2 Comparison of step response between exact‐ and pseudo‐derivative...
Figure 12.3 Concepts of (a) general differential operations and (b) velocity...
Figure 12.4 Conceptual diagram of and methods.
Figure 12.5 Algorithm of the method.
Figure 12.6 Response of the number of pulses in the experiment. (a) Low‐velo...
Figure 12.7 Algorithm for synchronous counting method.
Figure 12.8 Instantaneous speed observer algorithm.
Appendix A
Figure A.1 Block diagram of the PI velocity control system of a cart.
Figure A.2 Block diagram of the PID position control system of a bogie.
Figure A.3 Structure of state feedback control system.
Figure A.4 Block diagram of control system with identity observer.
Figure A.5 Block diagram of the continuous system minimal order observer.
Figure A.6 Block diagram of continuous servo system.
Figure A.7 Block diagram of ...
Figure A.8 Digital waveforms.
Figure A.9 Structure of digital control system. (a) Actual structure and (b)...
Figure A.10 Digital servo system block diagram.
Figure A.11 Example of a range of constraints.
Figure A.12 Example of fmincon function output.
Figure A.13 An example of Simulink model.
Figure A.14 Example of Scope settings for drawing Simulink data. (a) Scope x...
Figure A.15 Drawing example. (a) Scope x waveform and (b) Scope y waveform....
Guide
Cover
Table of Contents
IEEE Press
Title Page
Copyright
Author's Note
Books in the IEEE Press Series on Control Systems Theory and Applications
About the Author
Preface
About the Companion Website
Begin Reading
Index
WILEY END USER LICENSE AGREEMENT
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Disturbance Observer for Advanced Motion Control with MATLAB/Simulink
Akira Shimada
Shibaura Institute of Technology, Tokyo, Japan
IEEE Press Series on Control Systems Theory and Applications Maria Domenica Di Benedetto, Series Editor
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Author's Note
It is our great pleasure to have a chance to publish the book “Disturbance Observer for Advanced Motion Control with MATLAB/Simulink” and introduce it to readers worldwide.
Disturbance observer (DOB) is an algorithm or a function for estimating disturbances well‐known to control engineers. Still, no book has been published that systematically and comprehensively explains its contents. For example, we can represent DOB with a transfer function or in a state-space representation.
Moreover, we can also design it as a digital system or use it in vibration or communication delay systems. Furthermore, we should consider the effects of noise and modeling errors when designing the system. This book includes all such problems and explains how to understand and handle these issues in an easy‐to‐understand manner with many examples using MATLAB/Simulink.
We initially published this book in Japanese in Autumn 2021 since we wanted to post it for Japanese control engineers and students. However, after the publishing, many friends, professors, and engineers recommended that I should publish it in English for engineers and students worldwide. This publication is a response to their strong encouragement.
The contents of this English version are the same as those of the Japanese version, but I revised all programs and the Simulink model using the MATLAB/Simulink R2022a version to make them clear for readers. The readers can download all sample programs from Wiley's home page.
Moreover, I initially selected many references written in Japanese. However, they are not convenient for readers worldwide. Therefore I reselected books and articles written in English.
We sincerely hope this book becomes helpful for you.
Books in the IEEE Press Series on Control Systems Theory and Applications
Series Editor: Maria Domenica Di Benedetto, University of l'Aquila, Italy
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Feng Liu, ZhaojianWang, Changhong Zhao, and Peng Yang
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Disturbance Observer for Advanced Motion Control with MATLAB/Simulink
Akira Shimada
About the Author
Dr. Akira Shimada was born in Chiba, Japan, in 1958. He received B.S. degree in electronics engineering from the University of Electro‐Communications, Japan, in 1983 and received PhD in engineering from Keio University, Japan, in 1996. After graduation, he worked as a robotics engineer at Seiko Instruments from 1983 to 2001. He developed some industrial robot controllers. His main contribution was to create digital servo control systems, including disturbance observers, and design DC and AC servo motor drivers. Concurrently, he was a guest professor at Chiba University. He was an associate professor at the Polytechnic University, Japan, from 2001 to 2009. He has been a full professor at Shibaura Institute of Technology, Japan, since 2009. His current interests include motion control, robotics, control engineering, and free climbing. The present study themes are motion control and path planning and collision avoidance for humanoid climbing robots, wheeled mobile robots, inverted pendulum robots, autonomous drones, etc. His philosophy for the study is to have actual and practical experience. When he studies cooking robots, he cooks a variety of foods. To develop climbing robots, he climbs existing walls in the mountains or climbing gyms every week. He is a member of IEEE, SICE, and RSJ and a senior member of IEEJ.
Preface
There is an estimation method called the “disturbance observer.” When some mechatronic systems move, friction, gravity, and external forces may disturb their motion. We refer to them collectively as disturbances. The disturbances are often unmeasurable, and the contents are unknown. If we can estimate the total value of these disturbances, we can improve the stability and tracking performance of the control system or use them in information processing. Generally, the term “observer” refers to a conference observer, but it is translated as “state observer” in control engineering and means a function for estimating state variables. The observer was proposed in 1964 by D. G. Luenberger, said to be a doctoral student at Stanford University then [1, 2]. The disturbance observer is an observer that estimates disturbances. Since the publication of the papers by Kiyoshi Ohishi, Kouhei Onishi, et al. [3] and Kouhei Ohnishi and Toshiyuki Murakami [4], they have attracted widespread attention and have been studied and applied by researchers and engineers worldwide [5–9]. Meditch and Hostetter [10] reported the design of a 0‐observer for estimating unknown stationary inputs and a ‐observer for estimating unknown inputs represented by ‐degree polynomials. The extended system for observer design is defined using the unknown input as in addition to the original state variable . Both and can be estimated according to the general observer theory if observability holds. This is not different from how we design disturbance observers in today's state space representation. Additionally, many papers have reported various unknown input estimation methods [11–16]. However, the name “disturbance observer” was invented by focusing intensely on the disturbance. Overall, “disturbance observer” includes almost complete disturbance suppression control by feeding back the disturbance estimate to cancel the disturbance, suppress parameter fluctuation, and control acceleration. It means that the “disturbance observer technology” is considered to have started with the papers [3, 4], and many others. This book aims to systematically describe the design process, application methods, and various properties of “disturbance observers” so that they can be helpful to many people who study control. In the design of disturbance observers for mechatronics system control, it is necessary to observe or calculate the position (or angle) or velocity (or angular velocity) information using sensors. It is essential to obtain highly accurate velocity information not affected by noise. We express our sincere thanks to Prof. Toshiaki Tsuji of Saitama University and Mr. Hiroyuki Nagatomi from Ohnishi Lab. They cooperated in writing the paper on velocity measurement and estimation techniques. The contents of this paper were tested in undergraduate and graduate classes, and then many suggestions were given by the members of the Motion Control Laboratory (Shimada Laboratory), especially Mr. Kenta Matsuo, Mr. Kazuki Tokushige, Mr. Katsumichi Takase, Mr. Ryoya Nakajima, and Ms. Yuka Kimura. In addition, Prof. Takashi Ohhira of Chuo University pointed out inadequacies in the descriptions and made many suggestions. Corona Publishing Co., Ltd. published this book as one of the new books solicited by the Society of Instrument and Control Engineers (SICE) in 2021. We express our sincere gratitude to Prof. Shiro Masuda of Tokyo Metropolitan University who was in charge of this book and the Publication Committee for their support in its completion. Finally, we thank Prof. Kouhei Ohnishi and many friends for their continual meetings and guidance.
References
1
David G. Luenberger: Observing the state of a linear system,
IEEE Transactions on Military Electronica
, Vol. 8, No. 2, 74–80, 1964.
2
George Ellis:
Observers in Control Systems: A Practical Guide
, Academic Press, 2014.
3
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4
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