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Design of Embedded Robust Control Systems Using MATLAB Simulink ....pdf
Cover
Copyright
Contents
Preface
1 Embedded control systems
1.1 Introduction
1.2 Structure and elements of embedded control systems
1.2.1 Typical block diagram
1.2.2 A/D and D/A conversion
1.2.3 Sensors
1.2.4 Actuators
1.2.5 Processors
1.2.6 Software
1.2.6.1 Operational systems
1.2.6.2 Protocols
1.3 Sampling and aliasing
1.4 Fixed-point arithmetic
1.4.1 Fixed-point numbers
1.4.2 Scaling
1.4.2.1 Binary-point-only scaling
1.4.2.2 Slope and bias scaling
1.4.2.3 Unspecified scaling
1.4.3 Range and precision
1.4.4 Fixed-point arithmetic operations
1.4.4.1 Addition and subtraction
1.4.4.2 Multiplication
1.5 Floating-point arithmetic
1.5.1 Floating-point numbers
1.5.2 IEEE arithmetic
1.5.3 Floating-point arithmetic operations
1.6 Quantization effects
1.6.1 Truncation and roundoff
1.6.2 Quantization errors in A/D conversion
1.7 Design stages
1.7.1 Controller design
1.7.2 Closed-loop system simulation
1.7.3 Embedded code generation
1.8 Hardware configuration
1.8.1 Microprocessing architectures
1.8.2 Hardware description language
1.8.3 Module level development
1.8.4 System level development
1.9 Software configuration
1.9.1 Board support package
1.9.2 Application programing interface
1.9.3 Code generation
1.9.4 Code validation
1.10 Notes and references
2 System modeling
2.1 Plant modeling
2.2 Linearization
2.2.1 Analytic linearization
2.2.2 Symbolic linearization
2.2.3 Numeric linearization
2.3 Discretization
2.3.1 Discrete-time models
2.3.2 Discrete-time frequency responses
2.3.3 Discretization of continuous-time models
2.3.4 Discretization of time delay systems
2.3.5 Choice of the sampling period
2.3.6 Discretization of nonlinear models
2.4 Stochastic modeling
2.4.1 Stochastic linear systems
2.4.2 Discretization of stochastic models
2.4.3 Optimal estimation
2.5 Plant identification
2.5.1 Identification of black box model
2.5.2 Identification of gray-box model
2.6 Uncertainty modeling
2.6.1 Structured uncertainty models
2.6.2 Representing uncertain models by LFT
2.6.3 Deriving uncertain state-space models from Simulink® models
2.6.4 Unstructured uncertainty models
2.6.5 Mixed uncertainty models
2.6.6 Discretization of uncertain models
2.6.7 Deriving uncertainty models by identification
2.7 Sensor modeling
2.7.1 Allan variance
2.7.2 Stochastic gyro model
2.7.3 Stochastic accelerometer model
2.7.4 Sensor data filtering
2.8 Notes and references
3 Performance requirements and design limitations
3.1 SISO closed-loop systems
3.2 Performance specifications of SISO systems
3.2.1 Time-domain specifications
3.2.2 Frequency-domain specifications
3.3 Trade-offs in the design of SISO systems
3.3.1 Limitations on S and T
3.3.2 Right half-plane poles and zeros
3.3.3 Limitations imposed by time delays
3.3.4 Limitations imposed by measurement noise
3.3.5 Limitations, imposed by disturbances
3.3.6 Limitations on control action
3.3.7 Limitations due to model errors
3.4 MIMO closed-loop systems
3.5 Performance specifications of MIMO systems
3.5.1 Using singular values for performance analysis
3.5.2 H∞ Norm of a system
3.5.3 Hankel norm
3.6 Trade-offs in the design of MIMO systems
3.6.1 Disturbance rejection
3.6.2 Noise suppression
3.6.3 Model errors
3.7 Uncertain systems
3.8 Robust-stability analysis
3.8.1 Unstructured uncertainty
3.8.2 Structured singular value
3.8.3 Robust-stability analysis with µ
3.9 Robust performance analysis
3.9.1 Using µ for robust performance analysis
3.9.2 Worst case gain
3.9.3 Worst case margin
3.10 Numerical issues in robustness analysis
3.11 Notes and references
4 Controller design
4.1 PID controller
4.2 LQG controller with integral action
4.2.1 Discrete-time LQG controller
4.2.2 Colored measurement noise
4.2.3 LQG controller with bias compensation
4.3 LQ regulator with H∞ filter
4.3.1 Discrete-time H∞ filter
4.3.2 H∞ Filter with bias compensation
4.4 H∞ Design
4.4.1 The H∞ design problem
4.4.2 Mixed-sensitivity H∞ control
4.4.3 Two degrees-of-freedom controllers
4.4.4 Numerical issues in H∞ design
4.5 µ Synthesis
4.5.1 The µ synthesis problem
4.5.2 Replacing µ with its upper bound
4.5.3 DK iteration
4.5.3.1 First step of DK iteration: holding D fixed
4.5.3.2 Second step of DK iteration: holding K fixed
4.5.4 Numerical issues in µ synthesis
4.6 Controller comparison
4.7 HIL simulation
4.8 Notes and references
5 Case study 1: embedded control of tank physical model
5.1 Hardware configuration of embedded control system
5.1.1 Water tank
5.1.2 ARDUINO MEGA 2560
5.1.3 Voltage divider
5.1.4 Relay block
5.2 Plant identification
5.3 LQR and LQG controllers design
5.4 H∞ Controller design
5.5 Experimental evaluation
5.6 Notes and references
6 Case study 2: robust control of miniature helicopter
6.1 Helicopter model
6.1.1 Nonlinear helicopter model
6.1.2 Linearized model
6.1.3 Uncertain model
6.2 µ Synthesis of attitude controller
6.2.1 Performance requirements
6.2.2 Controller design
6.2.3 Frequency responses
6.2.4 Transient responses of the linear system
6.2.5 Position controller design
6.3 Hardware-in-the-loop simulation
6.3.1 Nonlinear system simulation
6.3.2 HIL simulation setup
6.3.3 Results of HIL simulation
6.4 Notes and references
7 Case study 3: robust control of two-wheeled robot
7.1 Robot description
7.2 Closed-loop identification of robot model
7.2.1 Dynamic models from u to ɸ
7.2.2 Dynamic models from ɸ to θ
7.2.3 Dynamic model of the yaw motion
7.3 Derivation of uncertain models
7.3.1 Signal-based uncertainty representation
7.3.2 Input multiplicative uncertainty representation
7.4 LQG controller design
7.5 µ Controller design
7.6 Comparison of designed controllers
7.7 Experimental evaluation
7.8 Notes and references
Appendix A: Elements of matrix analysis
A.1 Vectors and matrices
A.2 Eigenvalues and eigenvectors
A.3 Singular value decomposition
A.4 Vector and matrix norms
A.4.1 Vector norms
A.4.2 Matrix norms
A.4.3 Relationships between matrix norms
A.5 Notes and references
Appendix B: Elements of linear system theory
B.1 Description
B.2 Stability
B.3 Controllability and observability
B.4 Lyapunov equations
B.5 Poles and zeros
B.6 Notes and references
Appendix C: Stochastic processes
C.1 Random variables
C.2 Stochastic processes
C.3 White noise
C.4 Gauss–Markov processes
C.5 Generation of white noise in MATLAB®
C.6 Notes and references
Appendix D: Identification of linear models
D.1 Identification of linear black-box model
D.1.1 Experiment design and input/output data acquisition
D.1.2 Model structure selection and parameters estimation
D.1.3 Model validation
D.1.3.1 Test consistency of model input–output behavior
D.1.3.2 Test of output signals
D.1.3.3 Test of parameters confidence interval
D.1.3.4 Pole zero test
D.1.3.5 Test of residuals
D.2 Identification of linear gray-box model
D.3 Notes and references
Appendix E: Interfacing IMU with target microcontroller
E.1 Driving SPI communication
E.2 Design of Simulink® interface block
Appendix F: Measuring angular velocity with hall encoder
References
Index
Back Cover
IET CONTROL, ROBOTICS AND SENSORS SERIES 113
Design of Embedded Robust
Control Systems Using
MATLAB®/Simulink®
Other volumes in this series:
S. Spurgeon (Editors)
and L. Vlacic
(Editors)
A History of Control Engineering, 1800–1930 S. Bennett
Volume 8
Volume 18 Applied Control Theory, 2nd Edition J.R. Leigh
Volume 20 Design of Modern Control Systems D.J. Bell, P.A. Cook and N. Munro (Editors)
Volume 28 Robots and Automated Manufacture J. Billingsley (Editor)
Volume 33 Temperature Measurement and Control J.R. Leigh
Volume 34 Singular Perturbation Methodology in Control Systems D.S. Naidu
Volume 35 Implementation of Self-Tuning Controllers K. Warwick (Editor)
Volume 37 Industrial Digital Control Systems, 2nd Edition K. Warwick and D. Rees (Editors)
Volume 39 Continuous Time Controller Design R. Balasubramanian
Volume 40 Deterministic Control of Uncertain Systems A.S.I. Zinober (Editor)
Volume 41 Computer Control of Real-Time Processes S. Bennett and G.S. Virk (Editors)
Volume 42 Digital Signal Processing: Principles, devices and applications N.B. Jones and J.D. McK. Watson
(Editors)
Volume 44 Knowledge-Based Systems for Industrial Control J. McGhee, M.J. Grimble and A. Mowforth (Editors)
Volume 47 A History of Control Engineering, 1930–1956 S. Bennett
Volume 49 Polynomial Methods in Optimal Control and Filtering K.J. Hunt (Editor)
Volume 50 Programming Industrial Control Systems Using IEC 1131-3 R.W. Lewis
Volume 51 Advanced Robotics and Intelligent Machines J.O. Gray and D.G. Caldwell (Editors)
Volume 52 Adaptive Prediction and Predictive Control P.P. Kanjilal
Volume 53 Neural Network Applications in Control G.W. Irwin, K. Warwick and K.J. Hunt (Editors)
Volume 54 Control Engineering Solutions: A practical approach P. Albertos, R. Strietzel and N. Mort (Editors)
Volume 55 Genetic Algorithms in Engineering Systems A.M.S. Zalzala and P.J. Fleming (Editors)
Volume 56 Symbolic Methods in Control System Analysis and Design N. Munro (Editor)
Volume 57 Flight Control Systems R.W. Pratt (Editor)
Volume 58 Power-Plant Control and Instrumentation: The control of boilers and HRSG systems D. Lindsley
Volume 59 Modelling Control Systems Using IEC 61499 R. Lewis
Volume 60 People in Control: Human factors in control room design J. Noyes and M. Bransby (Editors)
Volume 61 Nonlinear Predictive Control: Theory and practice B. Kouvaritakis and M. Cannon (Editors)
Volume 62 Active Sound and Vibration Control M.O. Tokhi and S.M. Veres
Volume 63 Stepping Motors, 4th Edition P.P. Acarnley
Volume 64 Control Theory, 2nd Edition J.R. Leigh
Volume 65 Modelling and Parameter Estimation of Dynamic Systems J.R. Raol, G. Girija and J. Singh
Volume 66 Variable Structure Systems: From principles to implementation A. Sabanovic, L. Fridman and
Volume 67 Motion Vision: Design of compact motion sensing solution for autonomous systems J. Kolodko
Volume 68 Flexible Robot Manipulators: Modelling, simulation and control M.O. Tokhi and A.K.M. Azad
Volume 69 Advances in Unmanned Marine Vehicles G. Roberts and R. Sutton (Editors)
Volume 70 Intelligent Control Systems Using Computational Intelligence Techniques A. Ruano (Editor)
Volume 71 Advances in Cognitive Systems S. Nefti and J. Gray (Editors)
Volume 72 Control Theory: A guided tour, 3rd Edition J.R. Leigh
Volume 73 Adaptive Sampling with Mobile WSN K. Sreenath, M.F. Mysorewala, D.O. Popa and F.L. Lewis
Volume 74 Eigenstructure Control Algorithms: Applications to aircraft/rotorcraft handling qualities design
S. Srinathkumar
(Editors)
Volume 75 Advanced Control for Constrained Processes and Systems F. Garelli, R.J. Mantz and H. De Battista
Volume 76 Developments in Control Theory towards Global Control L. Qiu, J. Chen, T. Iwasaki and H. Fujioka
Volume 77 Further Advances in Unmanned Marine Vehicles G.N. Roberts and R. Sutton (Editors)
Volume 78 Frequency-Domain Control Design for High-Performance Systems J. O’Brien
Volume 80 Control-Oriented Modelling and Identification: Theory and practice M. Lovera (Editor)
Volume 81 Optimal Adaptive Control and Differential Games by Reinforcement Learning Principles
D. Vrabie, K. Vamvoudakis and F. Lewis
D. DeHaan
Volume 83 Robust and Adaptive Model Predictive Control of Nonlinear Systems M. Guay, V. Adetola and
Volume 84 Nonlinear and Adaptive Control Systems Z. Ding
Volume 86 Modeling and Control of Flexible Robot Manipulators, 2nd edition M.O. Tokhi and A.K.M. Azad
Volume 88 Distributed Control and Filtering for Industrial Systems M. Mahmoud
Volume 89 Control-Based Operating System Design A. Leva et al.
Volume 90 Application of Dimensional Analysis in Systems Modelling and Control Design P. Balaguer
Volume 91 An Introduction to Fractional Control D. Valério and J. Costa
Volume 92 Handbook of Vehicle Suspension Control Systems H. Liu, H. Gao and P. Li
Volume 93 Design and Development of Multi-Lane Smart Electromechanical Actuators F.Y. Annaz
Volume 94 Analysis and Design of Reset Control Systems Y. Guo, L. Xie and Y. Wang
Volume 95 Modelling Control Systems Using IEC 61499, 2nd Edition R. Lewis and A. Zoitl
Volume 96 Cyber-Physical System Design with Sensor Networking Technologies S. Zeadally and N. Jabeur
(Editors)
A.M. Galhano
Volume 99 Practical Robotics and Mechatronics: Marine, space and medical applications I. Yamamoto
Volume 100 Organic Sensors: Materials and applications E. Garcia-Breijo and P. Cosseddu (Editors)
Volume 102 Recent Trends in Sliding Mode Control L. Fridman J.P. Barbot and F. Plestan (Editors)
Volume 104 Control of Mechatronic Systems L. Guvenc, B.A. Guvenc, B. Demirel and M.T Emirler
Volume 105 Mechatronic Hands: Prosthetic and robotic design P.H. Chappell
Volume 107 Solved Problems in Dynamical Systems and Control D. Valério, J.T. Machado, A.M. Lopes and
Volume 108 Wearable Exoskeleton Systems: Design, control and applications S. Bai, G.S. Virk and T.G. Sugar
Volume 111 The Inverted Pendulum in Control Theory and Robotics: From theory to new innovations
Volume 112 RFID Protocol Design, Optimization, and Security for the Internet of Things Alex X. Liu,
O. Boubaker and R. Iriarte (Editors)
Muhammad Shahzad, Xiulong Liu and Keqiu Li
Design of Embedded Robust
Control Systems Using
MATLAB®/Simulink®
Petko H. Petkov, Tsonyo N. Slavov and Jordan K. Kralev
The Institution of Engineering and Technology
Published by The Institution of Engineering and Technology, London, United Kingdom
The Institution of Engineering and Technology is registered as a Charity in England &
Wales (no. 211014) and Scotland (no. SC038698).
© The Institution of Engineering and Technology 2018
First published 2018
This publication is copyright under the Berne Convention and the Universal Copyright
Convention. All rights reserved. Apart from any fair dealing for the purposes of research
or private study, or criticism or review, as permitted under the Copyright, Designs and
Patents Act 1988, this publication may be reproduced, stored or transmitted, in any
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the case of reprographic reproduction in accordance with the terms of licences issued
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terms should be sent to the publisher at the undermentioned address:
The Institution of Engineering and Technology
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www.theiet.org
While the authors and publisher believe that the information and guidance given in this
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To our teachers and students
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Contents
Preface
1 Embedded control systems
1.1 Introduction
1.2 Structure and elements of embedded control systems
1.2.1 Typical block diagram
1.2.2 A/D and D/A conversion
1.2.3 Sensors
1.2.4 Actuators
1.2.5 Processors
1.2.6 Software
1.3 Sampling and aliasing
1.4 Fixed-point arithmetic
1.4.1 Fixed-point numbers
1.4.2 Scaling
1.4.3 Range and precision
1.4.4 Fixed-point arithmetic operations
1.5 Floating-point arithmetic
1.5.1 Floating-point numbers
1.5.2 IEEE arithmetic
1.5.3 Floating-point arithmetic operations
1.6 Quantization effects
1.6.1 Truncation and roundoff
1.6.2 Quantization errors in A/D conversion
1.7 Design stages
1.7.1 Controller design
1.7.2 Closed-loop system simulation
1.7.3 Embedded code generation
1.8 Hardware configuration
1.8.1 Microprocessing architectures
1.8.2 Hardware description language
1.8.3 Module level development
1.8.4 System level development
1.9 Software configuration
1.9.1 Board support package
1.9.2 Application programing interface
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