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Physiological control systems : analysis, simulation, and estimation / Michael C.K. Khoo.

By: Khoo, Michael C. K [author.].
Contributor(s): IEEE Xplore (Online Service) [distributor.] | Wiley [publisher.] | IEEE Engineering in Medicine and Biology Society [sponsoring body.].
Material type: materialTypeLabelBookSeries: IEEE Press series in biomedical engineering: 28.Publisher: Piscataway, New Jersey : Hoboken, New Jersey : IEEE Press ; Wiley, [2018]Distributor: [Piscataqay, New Jersey] : IEEE Xplore, [2018]Edition: Second editon.Description: 1 PDF (xvii, 429 pages) : illustrations.Content type: text Media type: electronic Carrier type: online resourceISBN: 9781119058793; 1119055334.Subject(s): Physiology -- Mathematical models | Biological control systems -- Mathematical models | Physiological Phenomena | Biomedical Engineering -- methods | Models, BiologicalGenre/Form: Electronic books.DDC classification: 612/.022 Online resources: Abstract with links to resource Also available in print.
Contents:
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���oInsulin 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���oOutput 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���oHurwitz 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���oHurwitz Analysis, 186 -- 6.6.2 Nyquist Analysis, 187 -- 6.7 Model of Cheyne���oStokes 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���oLung Preparation, 253 -- 8.4.2 Kao���Os 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���oHuxley Model, 349 -- 10.5.2 The Bonhoeffer���ovan der Pol Model, 352 -- 10.6 Nonparametric Identification of Nonlinear Systems, 359 -- 10.6.1 Volterra���oWiener 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.
Summary: "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."-
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Includes bibliographical references and index.

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���oInsulin 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���oOutput 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���oHurwitz 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���oHurwitz Analysis, 186 -- 6.6.2 Nyquist Analysis, 187 -- 6.7 Model of Cheyne���oStokes 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���oLung Preparation, 253 -- 8.4.2 Kao���Os 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���oHuxley Model, 349 -- 10.5.2 The Bonhoeffer���ovan der Pol Model, 352 -- 10.6 Nonparametric Identification of Nonlinear Systems, 359 -- 10.6.1 Volterra���oWiener 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.

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"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."-

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