Details

Physiological Control Systems


Physiological Control Systems

Analysis, Simulation, and Estimation
IEEE Press Series on Biomedical Engineering 2. Aufl.

von: Michael C. K. Khoo

103,99 €

Verlag: Wiley-IEEE Press
Format: PDF
Veröffentl.: 12.04.2018
ISBN/EAN: 9781119058793
Sprache: englisch
Anzahl Seiten: 456

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Beschreibungen

A guide to common control principles and how they are used to characterize a variety of physiological mechanisms The second edition of Physiological Control Systems offers an updated and comprehensive resource that reviews the fundamental concepts of classical control theory and how engineering methodology can be applied to obtain a quantitative understanding of physiological systems. The revised text also contains more advanced topics that feature applications to physiology of nonlinear dynamics, parameter estimation methods, and adaptive estimation and control. The author—a noted expert in the field—includes a wealth of worked examples that illustrate key concepts and methodology and offers in-depth analyses of selected physiological control models that highlight the topics presented. The author discusses the most noteworthy developments in system identification, optimal control, and nonlinear dynamical analysis and targets recent bioengineering advances. Designed to be a practical resource, the text includes guided experiments with simulation models (using Simulink/Matlab). Physiological Control Systems focuses on common control principles that can be used to characterize a broad variety of physiological mechanisms. This revised resource: Offers new sections that explore identification of nonlinear and time-varying systems, and provide the background for understanding the link between continuous-time and discrete-time dynamic models Presents helpful, hands-on experimentation with computer simulation models Contains fully updated problems and exercises at the end of each chapter Written for biomedical engineering students and biomedical scientists, Physiological Control Systems, offers an updated edition of this key resource for understanding classical control theory and its application to physiological systems. It also contains contemporary topics and methodologies that shape bioengineering research today. 
Preface xiii About the Companion Website xvii 1 Introduction 1 1.1 Preliminary Considerations, 1 1.2 Historical Background, 2 1.3 Systems Analysis: Fundamental Concepts, 4 1.4 Physiological Control Systems Analysis: A Simple Example, 6 1.5 Differences Between Engineering and Physiological Control Systems, 8 1.6 The Science (and Art) of Modeling, 11 1.7 “Systems Physiology” Versus “Systems Biology”, 12 Problems, 13 Bibliography, 15 2 Mathematical Modeling 17 2.1 Generalized System Properties, 17 2.2 Models with Combinations of System Elements, 21 2.3 Linear Models of Physiological Systems: Two Examples, 24 2.4 Conversions Between Electrical and Mechanical Analogs, 27 2.5 Distributed-Parameter Versus Lumped-Parameter Models, 29 2.6 Linear Systems and the Superposition Principle, 31 2.7 Zero-Input and Zero-State Solutions of ODEs, 33 2.8 Laplace Transforms and Transfer Functions, 34 2.8.1 Solving ODEs with Laplace Transforms, 36 2.9 The Impulse Response and Linear Convolution, 38 2.10 State-Space Analysis, 40 2.11 Computer Analysis and Simulation: MATLAB and SIMULINK, 43 Problems, 49 Bibliography, 53 3 Static Analysis of Physiological Systems 55 3.1 Introduction, 55 3.2 Open-Loop Versus Closed-Loop Systems, 56 3.3 Determination of the Steady-State Operating Point, 59 3.4 Steady-State Analysis Using SIMULINK, 63 3.5 Regulation of Cardiac Output, 66 3.5.1 The Cardiac Output Curve, 67 3.5.2 The Venous Return Curve, 69 3.5.3 Closed-Loop Analysis: Heart and Systemic Circulation Combined, 73 3.6 Regulation of Glucose Insulin, 74 3.7 Chemical Regulation of Ventilation, 78 3.7.1 The Gas Exchanger, 80 3.7.2 The Respiratory Controller, 82 3.7.3 Closed-Loop Analysis: Lungs and Controller Combined, 82 Problems, 86 Bibliography, 91 4 Time-Domain Analysis of Linear Control Systems 93 4.1 Linearized Respiratory Mechanics: Open-Loop Versus Closed-Loop, 93 4.2 Open-Loop Versus Closed-Loop Transient Responses: First-Order Model, 96 4.2.1 Impulse Response, 96 4.2.2 Step Response, 97 4.3 Open-Loop Versus Closed-Loop Transient Responses: Second-Order Model, 98 4.3.1 Impulse Responses, 98 4.3.2 Step Responses, 103 4.4 Descriptors of Impulse and Step Responses, 107 4.4.1 Generalized Second-Order Dynamics, 107 4.4.2 Transient Response Descriptors, 111 4.5 Open-Loop Versus Closed-Loop Dynamics: Other Considerations, 114 4.5.1 Reduction of the Effects of External Disturbances, 114 4.5.2 Reduction of the Effects of Parameter Variations, 115 4.5.3 Integral Control, 116 4.5.4 Derivative Feedback, 118 4.5.5 Minimizing Effect of External Disturbances by Feedforward Gain, 119 4.6 Transient Response Analysis Using MATLAB, 121 4.7 SIMULINK Application 1: Dynamics of Neuromuscular Reflex Motion, 122 4.7.1 A Model of Neuromuscular Reflex Motion, 122 4.7.2 SIMULINK Implementation, 126 4.8 SIMULINK Application 2: Dynamics of Glucose–Insulin Regulation, 127 4.8.1 The Model, 127 4.8.2 Simulations with the Model, 131 Problems, 131 Bibliography, 135 5 Frequency-Domain Analysis of Linear Control Systems 137 5.1 Steady-State Responses to Sinusoidal Inputs, 137 5.1.1 Open-Loop Frequency Response, 137 5.1.2 Closed-Loop Frequency Response, 141 5.1.3 Relationship between Transient and Frequency Responses, 143 5.2 Graphical Representations of Frequency Response, 145 5.2.1 Bode Plot Representation, 145 5.2.2 Nichols Charts, 147 5.2.3 Nyquist Plots, 148 5.3 Frequency-Domain Analysis Using MATLAB and SIMULINK, 152 5.3.1 Using MATLAB, 152 5.3.2 Using SIMULINK, 154 5.4 Estimation of Frequency Response from Input–Output Data, 156 5.4.1 Underlying Principles, 156 5.4.2 Physiological Application: Forced Oscillation Technique in Respiratory Mechanics, 157 5.5 Frequency Response of a Model of Circulatory Control, 159 5.5.1 The Model, 159 5.5.2 Simulations with the Model, 160 5.5.3 Frequency Response of the Model, 162 Problems, 164 Bibliography, 165 6 Stability Analysis: Linear Approaches 167 6.1 Stability and Transient Response, 167 6.2 Root Locus Plots, 170 6.3 Routh–Hurwitz Stability Criterion, 174 6.4 Nyquist Criterion for Stability, 176 6.5 Relative Stability, 181 6.6 Stability Analysis of the Pupillary Light Reflex, 184 6.6.1 Routh–Hurwitz Analysis, 186 6.6.2 Nyquist Analysis, 187 6.7 Model of Cheyne–Stokes Breathing, 190 6.7.1 CO2 Exchange in the Lungs, 190 6.7.2 Transport Delays, 192 6.7.3 Controller Responses, 193 6.7.4 Loop Transfer Functions, 193 6.7.5 Nyquist Stability Analysis Using MATLAB, 194 Problems, 196 Bibliography, 198 7 Digital Simulation of Continuous-Time Systems 199 7.1 Preliminary Considerations: Sampling and the Z-Transform, 199 7.2 Methods for Continuous-Time to Discrete-Time Conversion, 202 7.2.1 Impulse Invariance, 202 7.2.2 Forward Difference, 203 7.2.3 Backward Difference, 204 7.2.4 Bilinear Transformation, 205 7.3 Sampling, 207 7.4 Digital Simulation: Stability and Performance Considerations, 211 7.5 Physiological Application: The Integral Pulse Frequency Modulation Model, 216 Problems, 221 Bibliography, 224 8 Model Identification and Parameter Estimation 225 8.1 Basic Problems in Physiological System Analysis, 225 8.2 Nonparametric and Parametric Identification Methods, 228 8.2.1 Numerical Deconvolution, 228 8.2.2 Least-Squares Estimation, 230 8.2.3 Estimation Using Correlation Functions, 233 8.2.4 Estimation in the Frequency Domain, 235 8.2.5 Optimization Techniques, 237 8.3 Problems in Parameter Estimation: Identifiability and Input Design, 243 8.3.1 Structural Identifiability, 243 8.3.2 Sensitivity Analysis, 244 8.3.3 Input Design, 248 8.4 Identification of Closed-Loop Systems: “Opening the Loop”, 252 8.4.1 The Starling Heart–Lung Preparation, 253 8.4.2 Kao’s Cross-Circulation Experiments, 253 8.4.3 Artificial Brain Perfusion for Partitioning Central and Peripheral Chemoreflexes, 255 8.4.4 The Voltage Clamp, 256 8.4.5 Opening the Pupillary Reflex Loop, 257 8.4.6 Read Rebreathing Technique, 259 8.5 Identification Under Closed-Loop Conditions: Case Studies, 260 8.5.1 Minimal Model of Blood Glucose Regulation, 262 8.5.2 Closed-Loop Identification of the Respiratory Control System, 267 8.5.3 Closed-Loop Identification of Autonomic Control Using Multivariate ARX Models, 273 8.6 Identification of Physiological Systems Using Basis Functions, 276 8.6.1 Reducing Variance in the Parameter Estimates, 276 8.6.2 Use of Basis Functions, 277 8.6.3 Baroreflex and Respiratory Modulation of Heart Rate Variability, 279 Problems, 283 Bibliography, 285 9 Estimation and Control of Time-Varying Systems 289 9.1 Modeling Time-Varying Systems: Key Concepts, 289 9.2 Estimation of Models with Time-Varying Parameters, 293 9.2.1 Optimal Estimation: The Wiener Filter, 293 9.2.2 Adaptive Estimation: The LMS Algorithm, 294 9.2.3 Adaptive Estimation: The RLS Algorithm, 296 9.3 Estimation of Time-Varying Physiological Models, 300 9.3.1 Extending Adaptive Estimation Algorithms to Other Model Structures, 300 9.3.2 Adaptive Estimation of Pulmonary Gas Exchange, 300 9.3.3 Quantifying Transient Changes in Autonomic Cardiovascular Control, 304 9.4 Adaptive Control of Physiological Systems, 307 9.4.1 General Considerations, 307 9.4.2 Adaptive Buffering of Fluctuations in Arterial PCO2, 308 Problems, 313 Bibliography, 314 10 Nonlinear Analysis of Physiological Control Systems 317 10.1 Nonlinear Versus Linear Closed-Loop Systems, 317 10.2 Phase-Plane Analysis, 320 10.2.1 Local Stability: Singular Points, 322 10.2.2 Method of Isoclines, 325 10.3 Nonlinear Oscillators, 329 10.3.1 Limit Cycles, 329 10.3.2 The van der Pol Oscillator, 329 10.3.3 Modeling Cardiac Dysrhythmias, 336 10.4 The Describing Function Method, 342 10.4.1 Methodology, 342 10.4.2 Application: Periodic Breathing with Apnea, 345 10.5 Models of Neuronal Dynamics, 348 10.5.1 The Hodgkin–Huxley Model, 349 10.5.2 The Bonhoeffer–van der Pol Model, 352 10.6 Nonparametric Identification of Nonlinear Systems, 359 10.6.1 Volterra–Wiener Kernel Approach, 360 10.6.2 Nonlinear Model of Baroreflex and Respiratory Modulated Heart Rate, 364 10.6.3 Interpretations of Kernels, 367 10.6.4 Higher Order Nonlinearities and Block-Structured Models, 369 Problems, 370 Bibliography, 374 11 Complex Dynamics in Physiological Control Systems 377 11.1 Spontaneous Variability, 377 11.2 Nonlinear Control Systems with Delayed Feedback, 380 11.2.1 The Logistic Equation, 380 11.2.2 Regulation of Neutrophil Density, 384 11.2.3 Model of Cardiovascular Variability, 387 11.3 Coupled Nonlinear Oscillators: Model of Circadian Rhythms, 397 11.4 Time-Varying Physiological Closed-Loop Systems: Sleep Apnea Model, 401 11.5 Propagation of System Noise in Feedback Loops, 409 Problems, 415 Bibliography, 416 Appendix A Commonly Used Laplace Transform Pairs 419 Appendix B List of MATLAB and SIMULINK Programs 421 Index 425
MICHAEL C.K. KHOO is a Professor of Biomedical Engineering and Pediatrics in the Biomedical Engineering Department at the University of Southern California. He is a fellow of the IEEE, Biomedical Engineering Society, the American Institute of Medical and Biological Engineering, and the International Academy of Medical and Biological Engineering.
A guide to key control principles and how they are used to characterize a variety of physiological mechanisms The second edition of Physiological Control Systems offers an updated and comprehensive resource that reviews the fundamental concepts of classical control theory and how engineering methodology can be applied to obtain a quantitative understanding of physiological systems. The revised text also contains more advanced topics that feature applications of linear and nonlinear dynamic analyses to physiology, parameter estimation methods, and adaptive estimation and control. The author—a noted expert in the field—includes a wealth of worked examples that illustrate key concepts and methodology and offers in-depth analyses of selected physiological control models that highlight the topics presented. The author discusses the most noteworthy developments in system identification, optimal control, and nonlinear dynamical analysis and targets recent bioengineering advances. Designed to be a practical resource, the text includes guided experiments with simulation models (using Simulink/Matlab). Physiological Control Systems focuses on basic control principles that can be used to characterize a broad variety of physiological mechanisms. This revised resource: Offers new sections that explore identification of nonlinear and time-varying systems, and provide the background for understanding the link between continuous-time and discrete-time dynamic models Presents helpful, hands-on experimentation with computer simulation models Contains fully updated problems and exercises at the end of each chapter Written for biomedical engineering students and biomedical scientists, Physiological Control Systems covers classical control theory and its application to physiological systems. It also contains contemporary topics and methodologies that shape bioengineering research today.

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