Robust and Adaptive Control

Höfundar: Eugene Lavretsky; Kevin A. Wise (Útgáfa: 2)
Robust and Adaptive Control

Kaup valmöguleikar

Robust and Adaptive Control (second edition) shows readers how to produce consistent and accurate controllers that operate in the presence of uncertainties and unforeseen events. Driven by aerospace applications, the focus of the book is primarily on continuous-time dynamical systems. The two-part text begins with robust and optimal linear control methods and moves on to a self-contained presentation of the design and analysis of model reference adaptive control for nonlinear uncertain dynamical systems.

Features of the second edition include:   sufficient conditions for closed-loop stability under output feedback observer-based loop-transfer recovery (OBLTR) with adaptive augmentation; OBLTR applications to aerospace systems; case studies that demonstrate the benefits of robust and adaptive control for piloted, autonomous and experimental aerial platforms; realistic examples and simulation data illustrating key featuresof the methods described; and problem solutions for instructors and MATLAB® code provided electronically.

The theory and practical applications address real-life aerospace problems, being based on numerous transitions of control-theoretic results into operational systems and airborne vehicles drawn from the authors’ extensive professional experience with The Boeing Company. The systems covered are challenging—often open-loop unstable with uncertainties in their dynamics—and thus require both persistently reliable control and the ability to track commands either from a pilot or a guidance computer.

Readers should have a basic understanding of root locus, Bode diagrams, and Nyquist plots, as well as linear algebra, ordinary differential equations, and the use of state-space methods in analysis and modeling of dynamical systems. The second edition contains a background summary of linear systems and control systems and an introduction to state observers and output feedback control, helping to make it self-contained.

Robust and Adaptive Control teaches senior undergraduate and graduate students how to construct stable and predictable control algorithms for realistic industrial applications. Practicing engineers and academic researchers will also find the book of great instructional value. The solutions manual can be accessed by instructors who have adopted this book for their courses at https://sites. google. com/springernature.

com/extramaterial/lecturer-material. To find the electronic supplementary material go to the publisher's website at https://link. springer. com/book/10. 1007/978-3-031-38314-4. Please go to the Table of contents”, to the chapter page linked through the title "Introduction" for ESM related to the chapters in Part I and to the chapter page linked through the title "Direct Model Reference Adaptive Control: Motivation and Introduction" for ESM related to Part II.

Nánar um bókina

Útgefandi
Springer Nature
ISBN
9783031383144
Print ISBN
9783031383137
Format
ePub
Útgáfa
2
Höfundar
Eugene Lavretsky; Kevin A. Wise
Tungumál
English
Útgefið
2024-02-20
Prent takmörkun á líftíma
100
Prent takmörkun
2
Afritunar takmörkun
2

Kaflar

  • Advanced Textbooks in Control and Signal Processing
  • Robust and Adaptive Control
  • Series Editor’s Foreword to the Second Edition
  • Preface to the Second Edition
  • Preface to the First Edition
  • Acknowledgments
  • Contents
  • Part I: Robust Control
  • 1. Introduction
  • 1.1 Why Robust and Adaptive Control?
  • 1.2 About This Book
  • 1.3 Aircraft Flight Dynamics Equations of Motion
  • 1.4 High-Fidelity Flight Simulation Environment
  • 1.5 Simplified Flight Dynamics for Control Design
  • 1.6 Summary
  • 1.7 Exercises
  • 2. Linear Time-Invariant Systems and Control
  • 2.1 Model-Based Control Engineering
  • 2.2 Control System Design Goals and Objectives
  • 2.3 Feedback and Feedforward Control
  • 2.4 State-Space Systems
  • 2.4.1 Time and Frequency Domain Modeling of State-Space Systems
  • 2.4.1.1 Time Domain Modeling of LTI Systems
  • 2.4.1.2 Frequency Domain Modeling of LTI Systems
  • 2.4.1.3 Transfer Functions, Block Diagrams, and the Root Locus
  • 2.4.1.4 Common Transfer Functions for Building Controllers
  • 2.4.1.5 Modeling Systems and Subsystems with Transfer Functions
  • 2.4.2 Control-Oriented Models for Linear Time-Invariant Systems
  • 2.4.3 State-Space Similarity Transformations
  • 2.4.4 Eigenvalues and Eigenvectors
  • 2.4.5 Computing the State Transition Matrix
  • 2.5 Stability, Controllability, and Observability
  • 2.5.1 Stability of LTI Systems
  • 2.5.2 Controllability of LTI Systems
  • 2.5.3 Observability of LTI Systems
  • 2.6 Norms of Vectors and Matrices in Euclidean Spaces
  • 2.7 Summary
  • 2.8 Exercises
  • 3. Frequency Domain Analysis
  • 3.1 Introduction
  • 3.2 Transfer Functions and Transfer Function Matrices
  • 3.3 Multivariable Stability Margins
  • 3.3.1 Singular Values
  • 3.3.2 Multivariable Nyquist Theory
  • 3.3.3 Singular Value-Based Stability Margins for MIMO Systems
  • 3.4 Control System Robustness Analysis
  • 3.4.1 Analysis Models for Uncertain Systems
  • 3.4.2 Singular Value Robustness Tests
  • 3.4.2.1 The Small Gain Theorem
  • 3.4.2.2 The Structured Singular Value μ
  • 3.4.3 Real Stability Margin
  • 3.5 Conclusions
  • 3.6 Exercises
  • 4. Optimal Control and Linear Quadratic Regulators
  • 4.1 Introduction
  • 4.2 Optimal Control and the Hamilton–Jacobi–Bellman Equation
  • 4.2.1 The HJB Equation for Nonlinear Systems Affine in Control
  • 4.3 Linear Quadratic Regulator (LQR)
  • 4.3.1 Infinite-Time LQR Problem
  • 4.3.2 Guaranteed Stability Robustness for State Feedback LQR
  • 4.3.3 LQR Design and Asymptotic Properties
  • 4.4 Command Tracking and Robust Servomechanism Control
  • 4.4.1 Servomechanism Control Design Model
  • 4.4.2 Servomechanism Model Controllability
  • 4.4.3 Servomechanism Control Design
  • 4.5 Conclusions
  • 4.6 Exercises
  • 5. State Feedback H∞ Optimal Control
  • 5.1 Introduction
  • 5.2 Norms for Signals and Systems
  • 5.3 Stability and Performance Specifications in the Frequency Domain
  • 5.4 Loop Shaping Using Frequency-Dependent Weights
  • 5.5 State Feedback H∞ Optimal Control
  • 5.6 Controller Design Using γ-Iteration
  • 5.7 Conclusions
  • 5.8 Exercises
  • 6. Output Feedback Control and State Observers
  • 6.1 Output Feedback Using Projective Controls
  • 6.2 Full-Order State Observers for Linear Time-Invariant Systems
  • 6.2.1 The Separation Principle
  • 6.2.2 Observer-Based Optimal Servomechanism Design
  • 6.2.3 Asymptotic Properties of the Algebraic Riccati Equation
  • 6.2.4 The Squaring-Up Method
  • 6.3 Observer-Based Control with Loop Transfer Recovery
  • 6.3.1 OBLTR Design Process and Examples
  • 6.4 Summary
  • 6.5 Exercises
  • Part II: Robust Adaptive Control
  • 7. Direct Model Reference Adaptive Control: Motivation and Introduction
  • 7.1 Model Reference Control: Motivational Example
  • 7.2 Introduction to Direct Model Reference Adaptive Control
  • 7.3 Direct Model Reference Adaptive Control of Scalar Linear Systems with Parametric Uncertainties
  • 7.4 Historical Roots and Foundations of Model Reference Adaptive Control
  • 7.5 Exercises
  • 8. Lyapunov Stability of Motion
  • 8.1 Dynamical Systems
  • 8.2 Existence and Uniqueness of Solutions
  • 8.3 System Equilibrium
  • 8.4 Lyapunov Stability Definitions
  • 8.5 Lyapunov Stability Theorems
  • 8.6 Uniform Ultimate Boundedness
  • 8.7 Barbalat’s Lemma
  • 8.8 Summary and Historical Remarks
  • 8.9 Exercises
  • 9. State Feedback Direct Model Reference Adaptive Control
  • 9.1 Introduction
  • 9.2 Command Tracking
  • 9.3 Direct MRAC Design for Scalar Systems
  • 9.4 Dynamic Inversion MRAC Design for Scalar Systems
  • 9.5 MRAC Design for Multi-Input–Multi-Output Systems
  • 9.6 Summary
  • 9.7 Exercises
  • 10. Model Reference Adaptive Control with Integral Feedback Connections
  • 10.1 Introduction
  • 10.2 Control Design
  • 10.3 MRAC Augmentation of an Optimal Baseline Controller
  • 10.4 Summary
  • 10.5 Exercises
  • 11. Robust Adaptive Control
  • 11.1 MRAC Design in the Presence of Bounded Disturbances
  • 11.2 MRAC Design Modifications for Robustness
  • 11.2.1 The Dead-Zone Modification
  • 11.2.2 The σ-Modification
  • 11.2.3 The e-Modification
  • 11.3 The Projection Operator
  • 11.4 Projection-Based MRAC Design
  • 11.5 Summary and Discussion
  • 11.6 Exercises
  • 12. Approximation-Based Adaptive Control
  • 12.1 Motivation
  • 12.2 Basic Definitions
  • 12.3 Approximation Properties of Feedforward Neural Networks
  • 12.4 Adaptive Control with State Limiting Constraints
  • 12.5 Summary
  • 12.6 Exercises
  • 13. Adaptive Control with Improved Transient Dynamics
  • 13.1 Motivation
  • 13.2 Asymptotic Orders and Singular Perturbations
  • 13.3 Asymptotic Properties of the Algebraic Riccati Equation
  • 13.4 System Dynamics and Control Problem Formulation
  • 13.5 Observer-Like Model Reference Adaptive Control
  • 13.6 Transient Dynamics Analysis
  • 13.7 Summary
  • 13.8 Exercises
  • 14. Output Feedback Servomechanism with Observer-Based Loop Transfer Recovery and Adaptive Augmentation
  • 14.1 Introduction
  • 14.2 Optimal Control with “Cheap” Input and “Expensive” Output
  • 14.3 Optimal Cost Asymptotic Analysis
  • 14.4 ARE Asymptotic Analysis
  • 14.5 Adaptive Output Feedback Design and Analysis
  • 14.6 Adaptive Flight Control of a Flexible Transport Aircraft
  • 14.7 Design Case Study: Control of the “Respect the Unstable” Dynamics
  • 14.8 Design Case Study: (OBLTR + Adaptive) Flight Control of Aircraft MIMO Roll–Yaw Dynamics
  • 14.9 Conclusions
  • 14.10 Exercises
  • 15. Robust and Adaptive Output Feedback Control for Square Non-Minimum Phase Systems
  • 15.1 Introduction
  • 15.2 Problem Motivation
  • 15.3 The Squaring-Up Design for Non-Minimum Phase Systems with Arbitrary Relative Degree
  • 15.4 Observer-Based Loop Transfer Recovery (OBLTR) Servo-Controller for Square Systems
  • 15.5 Loop Transfer Recovery and OBLTR Stability Margins for Square Systems
  • 15.6 OBLTR Adaptive Augmentation for Square Non-Minimum Phase Systems
  • 15.7 Summary
  • 15.8 Exercises
  • Appendix A: Aircraft Flight Simulation (aFltSim) Software
  • A.1 Aircraft Flight Dynamics Equations of Motion
  • A.2 High-Fidelity Flight Simulation Environment
  • A.3 Simplified Flight Dynamics for Control Design
  • A.4 aFltSim Block Diagram Architecture and Calling Sequence
  • References
  • Index