Advanced Pid Control

Introduction 1(11) Introduction 1(1) Feedback 2(1) Simple Forms of Feedback 3(2) How the PID Controller Developed 5(2) Technology Changes and Knowledge Transfer 7(1) Outline of the Contents of the Book 8(2) Summary 10(1) Notes and References 10(2) Process Models 12(52) Introduction 12(1) Static Models 13(1) Dynamic Models 14(9) Feature-Based Models 23(5) Typical Process Models 28(16) Models for Disturbances 44(3) How to Obtain the Models 47(9) Model Reduction 56(5) Summary 61(1) Notes and References 62(2) PID Control 64(31) Introduction 64(1) The PID Controller 64(9) Filtering the Derivative 73(1) Set-Point Weighting 74(2) Integrator Windup 76(11) When Can PID Control Be Used? 87(5) Summary 92(1) Notes and References 93(2) Controller Design 95(44) Introduction 95(1) A Rich Variety of Control Problems 96(1) Feedback Fundamentals 96(6) Stability 102(7) Closed-Loop Poles and Zeros 109(2) The Sensitivity Functions 111(7) Robustness to Process Variations 118(4) Quantifying the Requirements 122(6) Classical Specifications 128(8) Summary 136(1) Notes and References 137(2) Feedforward Design 139(19) Introduction 139(1) Improved Set-Point Response 139(6) Set-Point Weighting 145(1) Neutral Feedforward 146(4) Fast Set-Point Response 150(4) Disturbance Attenuation 154(2) Summary 156(1) Notes and References 157(1) PID Design 158(67) Introduction 158(1) Ziegler-Nichols and Related Methods 159(10) Rule-Based Empirical Tuning 169(5) Pole Placement 174(12) Lambda Tuning 186(3) Algebraic Design 189(7) Optimization Methods 196(10) Robust Loop Shaping 206(15) Summary 221(1) Notes and References 222(3) A Ziegler-Nichols Replacement 225(41) Introduction 225(1) The Test Batch 226(2) PI Control 228(2) PID Control 230(8) Frequency Response Methods 238(4) PID Control Based on Second-Order Model 242(5) Comparison of the Methods 247(4) Measurement Noise and Filtering 251(2) Detuning 253(9) Summary 262(3) Notes and References 265(1) Predictive Control 266(27) Introduction 266(1) The Smith Predictor 267(4) Analysis of Smith Predictor Control 271(8) The PPI Controller 279(4) Predictors for Integrating Processes 283(2) Model Predictive Control 285(6) Summary 291(1) Notes and References 292(1) Automatic Tuning and Adaptation 293(36) Introduction 293(1) Process Knowledge 294(1) Adaptive Techniques 295(3) Model-Based Methods 298(4) Rule-Based Methods 302(2) Supervision of Adaptive Controllers 304(9) Iterative Feedback Tuning 313(3) Commercial Products 316(11) Summary 327(1) Notes and References 327(2) Loop and Performance Assessment 329(18) Introduction 329(1) Valves 329(5) Loop Assessment 334(2) Performance Assessment 336(8) Integrated Tuning and Diagnosis 344(1) Summary 345(1) Notes and References 346(1) Interaction 347(19) Introduction 347(1) Interaction of Simple Loops 347(7) Decoupling 354(6) Parallel Systems 360(4) Summary 364(1) Notes and References 365(1) Control Paradigms 366(41) Introduction 366(1) Bottom-Up and Top-Down Approaches 367(1) Repetitive Control 368(5) Cascade Control 373(5) Mid-Range and Split-Range Control 378(3) Nonlinear Elements 381(8) Neural Network Control 389(3) Fuzzy Control 392(6) System Structuring 398(6) Summary 404(2) Notes and References 406(1) Implementation 407(26) Introduction 407(1) Analog Implementations 408(4) Computer Implementations 412(8) Velocity Algorithms 420(3) Operational Aspects 423(4) Controller Outputs 427(4) Summary 431(1) Notes and References 432(1) Bibliography 433(23) Index 456