Title: The Control Handbook, 2nd Edition (3 Volume Set) Author: William S. Levine ISBN: 1420073664 / 9781420073669 Format: Hard Cover Pages: 3526 Publisher: CRC Press Year: 2011 Availability: Out of Stock
Description
Contents
At publication, The Control Handbook immediately became the definitive resource that engineers working with modern control systems required. Among its many accolades, that first edition was cited by the AAP as the Best Engineering Handbook of 1996.
Now, 15 years later, William Levine has once again compiled the most comprehensive and authoritative resource on control engineering. He has fully reorganized the text to reflect the technical advances achieved since the last edition and has expanded its contents to include the multidisciplinary perspective that is making control engineering a critical component in so many fields.
Now expanded from one to three volumes, The Control Handbook, Second Edition brilliantly organizes cutting-edge contributions from more than 200 leading experts representing every corner of the globe. They cover everything from basic closed-loop systems to multi-agent adaptive systems and from the control of electric motors to the control of complex networks. Progressively organized, the three volume set includes:
Control System Fundamentals
Control System Applications
Control System Advanced Methods
Any practicing engineer, student, or researcher working in fields as diverse as electronics, aeronautics, or biomedicine will find this handbook to be a time-saving resource filled with invaluable formulas, models, methods, and innovative thinking. In fact, any physicist, biologist, mathematician, or researcher in any number of fields developing or improving products and systems will find the answers and ideas they need. As with the first edition, the new edition not only stands as a record of accomplishment in control engineering but provides researchers with the means to make further advances.
Volume I : Control System Fundamentals
Preface
Acknowledgment
Editor
Contributors
Section I : Mathematical Foundations
Chapter 1 : Ordinary Linear Differential and Difference Equations Chapter 2 : The Fourier, Laplace, and z-Transforms Chapter 3 : Matrices and Linear Algebra Chapter 4 : Complex Variables
Section II : Models for Dynamical Systems Chapter 5 : Standard Mathematical Models Chapter 6 : Graphical Models
Section III : Analysis and Design Methods for Continuous-Time Systems
Chapter 7 : Analysis Methods Chapter 8 : Stability Tests Chapter 9 : Design Methods
Section IV : Digital Control
Chapter 10 : Discrete-Time Systems Chapter 11 : Sampled Data Systems Chapter 12 : Discrete-Time Equivalents to Continuous-Time Systems Chapter 13 : Design Methods for Discrete-Time, Linear Time-Invariant Systems Chapter 14 : Quantization Effects Chapter 15 : Sample-Rate Selection Chapter 16 : Real-Time Software for Implementation of Feedback Control Chapter 17 : Programmable Controllers
Section V : Analysis and Design Methods for Nonlinear Systems
Chapter 18 : Analysis Methods Chapter 19 : Design Methods
Index
Volume II : Control System Application
Preface
Acknowledgment
Editor
Contributors
Section I : Automotive
Chapter 1 : Linear Parameter-Varying Control of Continuous-Time Nonlinear Systems Chapter 2 : Powertrain Control Chapter 3 : Vehicle Controls Chapter 4 : Model-Based Supervisory Control for Energy Optimization of Hybrid-Electric Vehicles Chapter 5 : Purge Scheduling for Dead-Ended Anode Operation of PEM Fuel Cells
Section II : Aerospace
Chapter 6 : Aerospace Real-Time Control System and Software Chapter 7 : Stochastic Decision Making and Aerial Surveillance Control Strategies for Teams of Unmanned Aerial Vehicles Chapter 8 : Control Allocation Chapter 9 : Swarm Stability
Section III : Industrial
Chapter 10 : Control of Machine Tools and Machining Processes Chapter 11 : Process Control in Semiconductor Manufacturing Chapter 12 : Control of Polymerization Processes Chapter 13 : Multiscale Modeling and Control of Porous Thin Film Growth Chapter 14 : Control of Particulate processes Chapter 15 : Nonlinear Model Predictive Control for Batch Processes Chapter 16 : The Use of Multivariate Statistics in Process Control Chapter 17 : Plantwide Control Chapter 18 : Automation and Control Solutions for Flat Strip Metal Processing
Section IV : Biological and Medical
Chapter 19 : Model-Based Control of Biochemical Reactors Chapter 20 : Robotic Surgery Chapter 21 : Stochastic Gene Expression: Modeling, Analysis, and Identification Chapter 22 : Modeling the Human Body as a Dynamical System: Applications to Drug Discovery and Development
Section V : Electronics
Chapter 23 : Control of Brushless DC Motors Chapter 24 : Hybrid Model Predictive Control of the Boost Converter
Section VI : Networks
Chapter 25 : The SNR Approach to Networked Control Chapter 26 : Optimization and Control of Communication Networks
Section VII : Miscellaneous
Chapter 27 : Advanced Motion Control Design Chapter 28 : Color Controls: An Advanced Feedback System Chapter 29 : The Construction of Portfolios of Financial Assets: An Application of Optimal Stochastic Control Chapter 30 : Earthquake Response Control for Civil Structures Chapter 31 : Quantum Estimation and Control Chapter 32 : Motion Control of Marine Craft Chapter 33 : Control of Unstable Oscillations in Flows Chapter 34 : Modeling and Control of Air Conditioning and Refrigeration Systems
Index
Volume III : Control System Advanced Methods
Preface
Acknowledgment
Editor
Contributors
Section I : Analysis Methods for MIMO Linear Systems
Chapter 1 : Numerical and Computational Issues in Linear Control and System Theory Chapter 2 : Multivariable Poles, Zeros, and Pole-Zero Cancellations Chapter 3 : Fundamentals of Linear Time-Varying Systems Chapter 4 : Balanced Realizations, Model Order Reduction, and the Hankel Operator Chapter 5 : Geometric Theory of Linear Systems Chapter 6 : Polynomial and Matrix Fraction Descriptions Chapter 7 : Robustness Analysis with Real Parametric Uncertainty Chapter 8 : MIMO Frequency Response Analysis and the Singular Value Decomposition Chapter 9 : Stability Robustness to Unstructured Uncertainty for Linear Time Invariant Systems Chapter 10 : Trade-Offs and Limitations in Feedback Systems Chapter 11 : Modeling Deterministic Uncertainty
Section II : Kalman Filter and Observers
Chapter 12 : Linear Systems and White Noise Chapter 13 : Kalman Filtering Chapter 14 : Riccati Equations and their Solution Chapter 15 : Observers
Section III : Design Methods for MIMO LTI Systems
Chapter 16 : Eigenstructure Assignment Chapter 17 : Linear Quadratic Regulator Control Chapter 18 : H2 (LQG) and H8 Control Chapter 19 : l1 Robust Control: Theory, Computation, and Design Chapter 20 : The Structured Singular Value (µ) Framework Chapter 21 : Algebraic Design Methods Chapter 22 : Quantitative Feedback Theory (QFT) Technique Chapter 23 : Robust Servomechanism Problem Chapter 24 : Linear Matrix Inequalities in Control Chapter 25 : Optimal Control Chapter 26 : Decentralized Control Chapter 27 : Decoupling Chapter 28 : Linear Model Predictive Control in the Process Industries
Section IV : Analysis and Design of Hybrid Systems
Chapter 29 : Computation of Reach Sets for Dynamical Systems Chapter 30 : Hybrid Dynamical Systems: Stability and Stabilization Chapter 31 : Optimal Control of Switching Systems via Embedding into Continuous Optimal Control Problem
Section V : Adaptive Control
Chapter 32 : Automatic Tuning of PID Controllers Chapter 33 : Self-Tuning Control Chapter 34 : Model Reference Adaptive Control Chapter 35 : Robust Adaptive Control Chapter 36 : Iterative Learning Control
Section VI : Analysis and Design of Nonlinear Systems
Chapter 37 : Nonlinear Zero Dynamics Chapter 38 : The Lie Bracket and Control Chapter 39 : Two Timescale and Averaging Methods Chapter 40 : Volterra and Fliess Series Expansions for Nonlinear Systems Chapter 41 : Integral Quadratic Constraints Chapter 42 : Control of Nonholonomic and Underactuated Systems
Section VIII : Design
Chapter 46 : Feedback Linearization of Nonlinear Systems Chapter 47 : The Steady-State Behavior of a Nonlinear System Chapter 48 : Nonlinear Output Regulation Chapter 49 : Lyapunov Design Chapter 50 : Variable Structure, Sliding-Mode Controller Design Chapter 51 : Control of Bifurcations and Chaos Chapter 52 : Open-Loop Control Using Oscillatory Inputs Chapter 53 : Adaptive Nonlinear Control Chapter 54 : Intelligent Control Chapter 55 : Fuzzy Control Chapter 56 : Neural Control
Section IX : System Identification
Chapter 57 : System Identification
Section X : Stochastic Control
Chapter 58 : Discrete Time Markov Processes Chapter 59 : Stochastic Differential Equations Chapter 60 : Linear Stochastic Input–Output Models Chapter 61 : Dynamic Programming Chapter 62 : Approximate Dynamic Programming Chapter 63 : Stability of Stochastic Systems Chapter 64 : Continuous-Time Linear Systems Chapter 65 : Probabilistic and Randomized Tools for Control Design Chapter 66 : Stabilization of Stochastic Nonlinear Continuous-Time Systems
Section XI : Control of Distributed Parameter Systems
Chapter 67 : Control of Systems Governed by Partial Differential Equations Chapter 68 : Controllability of Thin Elastic Beams and Plates Chapter 69 : Control of the Heat Equation Chapter 70 : Observability of Linear Distributed-Parameter Systems Chapter 71 : Boundary Control of PDE’s: The Backstepping Approach Chapter 72 : Stabilization of Fluid Flows
Section XII : Networks and Networked Controls Chapter 73 : Control Over Digital Networks Chapter 74 : Decentralized Control and Algebraic Approaches Chapter 75 : Estimation and Control across Analog Erasure Channels Chapter 76 : Passivity Approach to Network Stability Analysis and Distributed Control Synthesis