Continous System Simulation
D.J. Murray-Smith · Chapman & Hall eBooks · 1995
Chapter 1 The Principles of Modelling: 1.1 Objectives in the modelling of systems 1.2 Continuous-variable and discrete-event models 1.3 Types of continuous-variable model 1.4 Modelling and simulation procedures for continuous-variable models. Chapter 2 An Introduction to Simulation Methods: 2.1 The need for simulation 2.2 Methods of simulation 2.2.1 Techniques based on special-purpose simulation hardware 2.2.2 Techniques based on general-purpose computer hardware 2.3 A review of simulation applications. Chapter 3 Problem Organisation for Continuous System Simulation: 3.1 Introduction 3.2 Descriptions for continuous-variable models - reduced and state variable forms 3.3 Conversion from reduced form to state-variable form 3.4 Transfer function descriptions 3.5 Bond graph representations 3.5.1 One-port components 3.5.2 Causality in bond graph representations 3.5.3 Junctions in bond graphs 3.5.4 Coupling between physical domains 3.5.5 Signals in bond graphs 3.5.6 Simulation program development from bond graph models 3.6 Block diagram and signal flow graph representations 3.7 Block diagram and signal flow graph methods for transfer function simulation 3.7.1 The direct construction approach 3.7.2 The parallel construction approach 3.7.3 The iterative construction approach 3.7.4 An example of block diagram construction from a transfer function 3.8 Modelling of distributed parameter elements 3.8.1 Introduction 3.8.2 Pure time delay 3.8.3 Distributed time delay 3.8.4 Simulation models involving pure and distributed delay elements 3.9 Parameter sensitivity analysis methods in system modelling and simulation 3.9.1 Methods for sensitivity cosystem simulation 3.9.1.1 Parameter sensitivity of linear models 3.9.1.2 Parameter sensitivity analysis in models containing nonlinear elements 3.10 Mathematical models of systems having both discrete and continuous elements. Chapter 4 The Principles of Numerical Modelling: 4.1 An introduction to numerical integration methods 4.2 Fixed-step integration algorithms - one-step methods 4.2.1 Introduction 4.2.2 Taylor series descriptions 4.2.3 Errors in fixed-step integration methods 4.2.4 Explicit Runge-Kutta methods 4.2.5 Trapezoidal integration 4.3 Fixed-step integration algorithms - multi-step methods 4.4 Problems of integration step size selection and numerical instability 4.5 Variable-step integration algorithms 4.6 Problems of stiff models 4.8 Discontinuities and their effects 4.9 Numerical methods for discontinuous problems 4.10 Problems of implicit loop structures. Chapter 5 Sampled-Data Models and Operator Methods: 5.1 Introduction 5.2 Approximations based on sampled-data theory 5.3 Modelling of linear systems using sampled-data approximations 5.3.1 Cascaded elements 5.3.2 Closed-loop systems 5.4 Modelling of non-linear systems using sampled-data approximations 5.4.1 Cascaded elements 5.4.2 Closed-loop models (part contents).