内容简介：　　　

　　Quantitative Process Control Theory explains how to solve industrial system problems using a novel control system design theory. This easy-to-use theory does not require designers to choose a weighting function and enables the controllers to be designed or tuned for quantitative engineering performance indices such as overshoot. In each chapter, a summary highlights the main problems and results and exercises improve and test your understanding of the material. Mathematical proofs are provided for almost all the results while examples are based on actual situations in industrial plants involving a paper-making machine, heat exchanger, hot strip mill, maglev, nuclear reactor, distillation column/heavy oil fractionator, jacket-cooled reactor, missile, helicopter/plane, and anesthesia. Developed from the author’s many years of research, this book takes a unique, practical approach for efficiently solving single-input and single-output (SISO) and multiple-input and multiple-output (MIMO) control system design issues for quantitative performance indices. With much of the material classroom-tested, the text is suitable for advanced undergraduate and graduate students in engineering, beginning researchers in robust control, and more seasoned engineers wanting to learn new design techniques.

英文目录：
1 Introduction
　　1.1 A Brief History of Control Theory
　　1.2 Design of Feedback Control Systems
　　1.3 Consideration on Control System Design
　　1.4 What This Book Is About
2 Classical Analysis Methods
　　2.1 Process Dynamic Responses
　　2.2 Rational Approximations of Time Delay
　　2.3 Time Domain Performance Indices
　　2.4 Frequency Response Analysis
　　2.5 Transformation of Two Commonly Used Models
　　2.6 Design Requirements and Controller Comparison
3 Essentials of the Robust Control Theory
　　3.1 Norms and System Gains
　　3.2 Internal Stability and Performance
　　3.3 Controller Parameterization
　　3.4 Robust Stability and Robust Performance
　　3.5 Robustness of the System with Time Delay
4 H∞ PID Controllers for Stable Plants
　　4.1 Traditional Design Methods
　　4.2 H∞ PID Controller for the First-Order Plant
　　4.3 The H∞ PID Controller and the Smith Predictor
　　4.4 Quantitative Performance and Robustness
　　4.5 H∞ PID Controller for the Second-Order Plant
　　4.6 All Stabilizing PID Controllers for Stable Plants
5 H2 PID Controllers for Stable Plants
　　5.1 H2 PID Controller for the First-Order Plant
　　5.2 Quantitative Tuning of H2 PID Controller
　　5.3 H2 PID Controller for the Second-Order Plant
　　5.4 Control of Inverse Response Processes
　　5.5 PID Controller Based on the Maclaurin Series Expansion
　　5.6 PID Controller with the Best Achievable Performance
　　5.7 Choice of the Filter
6 Control of Stable Plants
　　6.1 The Quasi-H∞ Smith Predictor
　　6.2 The H2 Optimal Controller and the Smith Predictor
　　6.3 Equivalents of the Optimal Controller
　　6.4 PID Controller and High-Order Controllers
　　6.5 Choice of the Weighting Function
　　6.6 Simplified Tuning for Quantitative Robustness
7 Control of Integrating Plants
　　7.1 Feature of Integrating Systems
　　7.2 H∞ PID Controller for Integrating Plants
　　7.3 H2 PID Controller for Integrating Plants
　　7.4 Controller Design for General Integrating Plants
　　7.5 Maclaurin PID Controller for Integrating Plants
　　7.6 The Best Achievable Performance of a PID Controller
8 Control of Unstable Plants
　　8.1 Controller Parameterization for General Plants
　　8.2 H∞ PID Controller for Unstable Plants
　　8.3 H2 PID Controller for Unstable Plants
　　8.4 Performance Limitation and Robustness
　　8.5 Maclaurin PID Controller for Unstable Plants
　　8.6 PID Design for the Best Achievable Performance
　　8.7 All Stabilizing PID Controllers for Unstable Plants
9 Complex Control Strategies
　　9.1 The 2DOF Structure for Stable Plants
　　9.2 The 2DOF Structure for Unstable Plants
　　9.3 Cascade Control
　　9.4 An Anti-Windup Structure
　　9.5 Feedforward Control
　　9.6 Optimal Input Disturbance Rejection
　　9.7 Control of Plants with Multiple Time Delays
10 Analysis of MIMO Systems
　　10.1 Zeros and Poles of a MIMO Plant
　　10.2 Singular Values
　　10.3 Norms for Signals and Systems
　　10.4 Nominal Stability and Performance
　　10.5 Robust Stability of MIMO Systems
　　10.6 Robust Performance of MIMO Systems
11 Classical Design Methods for MIMO Systems
　　11.1 Interaction Analysis
　　11.2 Decentralized Controller Design
　　11.3 Decoupler Design
12 Quasi-H∞ Decoupling Control
　　12.1 Diagonal Factorization for Quasi- H∞ Control
　　12.2 Quasi- H∞ Controller Design
　　12.3 Analysis for Quasi- H∞ Control Systems
　　12.4 Increasing Time Delays for Performance Improvement
　　12.5 A Design Example for Quasi- H∞ Control
　　12.6 Multivariable PID Controller Design
13 H2 Decoupling Control
　　13.1 Controller Parameterization for MIMO Systems
　　13.2 Diagonal Factorization for H2 Control
　　13.3 H2 Optimal Decoupling Control
　　13.4 Analysis for H2 Decoupling Control Systems
　　13.5 Design Examples for H2 Decoupling Control
14 Multivariable H2 Optimal Control
　　14.1 Factorization for Simple RHP Zeros
　　14.2 Construction Procedure of Factorization
　　14.3 Factorization for Multiple RHP Zeros
　　14.4 Analysis and Computation
　　14.5 Solution to the H2 Optimal Control Problem
　　14.6 Filter Design
　　14.7 Examples for H2 Optimal Controller Designs
Bibliography
Index