Passive macromodeling. (2015)

• Record Type: Book
• Further Information: Note: Stefano Grivet-Talocia, Bjøorn Gustavsen.
• Authors: Grivet-Talocia, Stefano, 1970-; Gustavsen, Bjørn, 1965-
• Contents: Preface xix 1 Introduction 1 1.1 Why Macromodeling? 1 1.2 Scope 4 1.3 Macromodeling Flows 6 1.3.1 Macromodeling via Model Order Reduction 6 1.3.2 Macromodeling from Field Solver Data 7 1.3.3 Macromodeling from Measured Responses 8 1.4 Rational Macromodeling 9 1.5 Physical Consistency Requirements 11 1.6 Time-Domain Implementation 15 1.7 An Example 16 1.8 What Can Go Wrong? 17 2 Linear Time-Invariant Circuits and Systems 23 2.1 Basic Definitions 24 2.1.1 Linearity 24 2.1.2 Memory and Causality 26 2.1.3 Time Invariance 26 2.1.4 Stability 27 2.1.5 Passivity 28 2.2 Linear Time-Invariant Systems 28 2.2.1 Impulse Response 29 2.2.2 Properties of LTI Systems 32 2.3 Frequency-Domain Characterizations 33 2.4 Laplace and Fourier Transforms 34 2.4.1 Bilateral Laplace Transform and Transfer Matrices 34 2.4.2 Causal LTI Systems and the Unilateral Laplace Transform 36 2.4.3 Fourier Transform 36 2.5 Signal and System Norms∗ 37 2.5.1 Signal Norms 38 2.5.2 System Norms 41 2.6 Multiport Representations 44 2.6.1 Ports and Terminals 44 2.6.2 Immittance Representations 45 2.6.3 Scattering Representations 46 2.6.4 Reciprocity 48 2.7 Passivity 49 2.7.1 Power and Energy 50 2.7.2 Passivity and Causality 51 2.7.3 The Static Case 52 2.7.4 The Dynamic Case 53 2.7.5 Positive Realness, Bounded Realness, and Passivity 54 2.7.6 Some Examples 56 2.8 Stability and Causality 59 2.8.1 Laplace-Domain Conditions for Causality 61 2.8.2 Laplace-Domain Conditions for BIBO Stability 62 2.8.3 Causality and Stability 62 2.9 Boundary Values and Dispersion Relations∗ 64 2.9.1 Assumptions 64 2.9.2 Reconstruction of H(s) for s ∈ C+ 65 2.9.3 Reconstruction of H(s) for s ∈ jR 65 2.9.4 Causality and Dispersion Relations 67 2.9.5 Generalizations 68 2.10 Passivity Conditions on the Imaginary Axis∗ 70 Problems 71 3 Lumped LTI Systems 73 3.1 An Example from Circuit Theory 74 3.1.1 Variation on a Theme 76 3.1.2 Driving-Point Impedance 77 3.2 State-Space and Descriptor Forms 77 3.2.1 Singular Descriptor Forms 77 3.2.2 Internal Representations of Lumped LTI Systems 79 3.3 The Zero-Input Response 80 3.4 Internal Stability 81 3.4.1 Lyapunov Stability 81 3.4.2 Internal Stability of LTI Systems 83 3.5 The Lyapunov Equation 84 3.6 The Zero-State Response 87 3.6.1 Impulse Response 88 3.7 Operations on State-Space Systems 89 3.7.1 Interconnections 90 3.7.2 Inversion 91 3.7.3 Similarity Transformations 91 3.8 Gramians 91 3.8.1 Observability 92 3.8.2 Controllability 93 3.8.3 Minimal Realizations 95 3.9 Reciprocal State-Space Systems 95 3.10 Norms 97 3.10.1 L2 Norm 98 3.10.2 H∞ Norm 99 Problems 100 4 Distributed LTI Systems 103 4.1 One-Dimensional Distributed Circuits 104 4.1.1 The Discrete-Space Case 104 4.1.2 The Continuous-Space Case 106 4.1.3 Discussion 109 4.2 Two-Dimensional Distributed Circuits∗ 111 4.2.1 The Discrete-Space Case 112 4.2.2 The Continuous-Space Case 114 4.2.3 A Closed-Form Solution 116 4.2.4 Spatial Discretization 118 4.2.5 Discussion 120 4.3 General Electromagnetic Characterization 123 4.3.1 3D Electromagnetic Modeling 126 4.3.2 Summary and Outlook 130 Problems 131 5 Macromodeling Via Model Order Reduction 135 5.1 Model Order Reduction 135 5.2 Moment Matching 136 5.2.1 Moments 136 5.2.2 Padé Approximation and AWE 138 5.2.3 Complex Frequency Hopping 139 5.3 Reduction by Projection 140 5.3.1 Krylov Subspaces 141 5.3.2 Implicit Moment Matching: The Orthogonal Case 142 5.3.3 The Arnoldi Process 143 5.3.4 PRIMA 145 5.3.5 Multipoint Moment Matching 147 5.3.6 An Example 148 5.3.7 Implicit Moment Matching: The Biorthogonal Case 151 5.3.8 Padé Via Lanczos (PVL) 154 5.4 Reduction by Truncation 155 5.4.1 Balancing 156 5.4.2 Balanced Truncation 158 5.5 Advanced Model Order Reduction∗ 159 5.5.1 Passivity-Preserving Balanced Truncation 159 5.5.2 Balanced Truncation of Descriptor Systems 160 5.5.3 Reducing Large-Scale Systems 161 Problems 166 6 Black-Box Macromodeling and Curve Fitting 169 6.1 Basic Curve Fitting 171 6.1.1 Linear Least Squares 172 6.1.2 Maximum Likelihood Estimation 174 6.1.3 Polynomial Fitting 176 6.2 Direct Rational Fitting 182 6.2.1 Polynomial Ratio Form 183 6.2.2 Pole–Zero Form 183 6.2.3 Partial Fraction Form 184 6.2.4 Partial Fraction Form with Fixed Poles 184 6.2.5 Nonlinear Least Squares 185 6.3 Linearization via Weighting 187 6.4 Asymptotic Pole–Zero Placement 191 6.5 ARMA Modeling 193 6.5.1 Modeling from Time-Domain Responses 195 6.5.2 Modeling from Frequency Domain Responses 197 6.5.3 Conversion of ARMA Models 201 6.6 Prony’s Method 203 6.7 Subspace-Based Identification∗ 204 6.7.1 Discrete-Time State-Space Systems 204 6.7.2 Macromodeling from Impulse Response Samples 205 6.7.3 Macromodeling from Input–Output Samples 207 6.7.4 From Discrete-Time to Continuous-Time State-Space Models 210 6.7.5 Frequency-Domain Subspace Identification 211 6.7.6 Generalized Pencil-of-Function Methods 212 6.7.7 Examples 214 6.8 Loewner Matrix Interpolation∗ 215 6.8.1 The Scalar Case 216 6.8.2 The Multiport Case 218 Problems 222 7 The Vector Fitting Algorithm 225 7.1 The Sanathanan–Koerner Iteration 226 7.1.1 The Steiglitz–McBride Iteration 229 7.2 The Generalized Sanathanan–Koerner Iteration 231 7.2.1 General Basis Functions 231 7.2.2 The Partial Fraction Basis 233 7.3 Frequency-Domain Vector Fitting 234 7.3.1 A Simple Model Transformation 234 7.3.2 Computing the New Poles 236 7.3.3 The Vector Fitting Iteration 237 7.3.4 From GSK to VF 239 7.4 Consistency And Convergence 241 7.4.1 Consistency 241 7.4.2 Convergence 242 7.4.3 Formal Convergence Analysis 245 7.5 Practical VF Implementation 247 7.5.1 Causality, Stability, and Realness 247 7.5.2 Order Selection and Initialization 253 7.5.3 Improving Numerical Robustness 254 7.6 Relaxed Vector Fitting 256 7.6.1 Weight Normalization, Noise, and Convergence 256 7.6.2 Relaxed Vector Fitting 259 7.7 Tuning VF 264 7.7.1 Weighting and Error Control 264 7.7.2 High-Frequency Behavior 266 7.7.3 High-Frequency Constraints 268 7.7.4 DC Point Enforcement 269 7.7.5 Simultaneous Constraints 271 7.8 Time-Domain Vector Fitting 273 7.9 z-Domain Vector Fitting 278 7.10 Orthonormal Vector Fitting 281 7.10.1 Orthonormal Rational Basis Functions 281 7.10.2 The OVF Iteration 284 7.10.3 The OVF Pole Relocation Step 285 7.10.4 Finding Residues 286 7.11 Other Variants 288 7.11.1 Magnitude Ve
• Edition: 1st
• Publisher Details: Hoboken, New Jersey : John Wiley & Sons, Inc
• Publication Date: 2015
• Extent: 1 online resource
• Subjects: 621.3011; Electromagnetic interference -- Computer simulation; Analog electronic systems -- Computer simulation; Electric power systems -- Computer simulation; Passive components -- Computer simulation
• Languages: English
• ISBNs: 9781119140955
• Related ISBNs: 9781118094914
• Notes: Note: Includes bibliographical references and index.; Note: Description based on CIP data; item not viewed.
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