Modelling and Simulation of Integrated Systems in Engineering

  • ID: 2719709
  • Book
  • Region: Global
  • 372 Pages
  • Elsevier Science and Technology
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This book places particular emphasis on issues of model quality and ideas of model testing and validation. Mathematical and computer-based models provide a foundation for explaining complex behaviour, decision-making, engineering design and for real-time simulators for research and training. Many engineering design techniques depend on suitable models, assessment of the adequacy of a given model for an intended application is therefore critically important. Generic model structures and dependable libraries of sub-models that can be applied repeatedly are increasingly important. Applications are drawn from the fields of mechanical, aeronautical and control engineering, and involve non-linear lumped-parameter models described by ordinary differential equations.
  • Focuses on issues of model quality and the suitability of a given model for a specific application
  • Multidisciplinary problems within engineering feature strongly in the applications
  • The development and testing of nonlinear dynamic models is given very strong emphasis
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List of figures

List of tables

List of abbreviations



About the author

Chapter 1: The principles of system modelling


1.1 General issues in the development and application of models

1.2 Classes of model for engineering applications

1.3 Questions of model quality

1.4 Methods of experimental modelling

1.5 Model reuse and generic models

1.6 Modelling within the procurement process

Chapter 2: Integrated systems and their significance for system modelling


2.1 An introduction to integrated systems

2.2 Sequential and concurrent design procedures

Chapter 3: Problem organisation


3.1 Model organisation for engineering systems design

3.2 The physical component layer

3.3 The physical concept layer

3.4 The mathematical description layer

3.5 Software for modelling and simulation

3.6 New developments in the modelling and simulation of micro-and nano-mechanical systems

Chapter 4: Inverse simulation for system modelling and design


4.1 An introduction to inverse modelling and inverse simulation

4.2 Methods of inverse simulation

4.3 Example: inverse simulation applied to a linear model

4.4 Case study: an application involving a nonlinear unmanned underwater vehicle (UUV) system model

4.5 Discussion

Chapter 5: Methods and applications of parameter sensitivity analysis


5.1 Fundamental concepts of parameter sensitivity analysis

5.2 The sensitivity function

5.3 Methods of sensitivity analysis involving repeated solutions

5.4 Methods of sensitivity analysis involving sensitivity models

5.5 Case study: sensitivity analysis applied to the unmanned underwater vehicle (UUV) model

5.6 Sensitivity analysis using bond graphs

5.7 Sensitivity analysis in inverse simulation

Chapter 6: Experimental modelling: system identification, parameter estimation and model optimisation techniques


6.1 The use of system identification and optimisation techniques in the development of physically based dynamic models

6.2 Applications of conventional methods of system identification and parameter estimation to physically based models

6.3 System identification and parameter estimation applied to helicopter flight mechanics models

6.4 Some selected methods of local and global parameter optimisation

6.5 Genetic programming (GP) for model structure estimation

6.6 Some practical issues in global parameter optimisation

6.7 Further examples of system identification, parameter estimation and model optimisation techniques in integrated systems applications

Chapter 7: Issues of model quality and the validation of dynamic models


7.1 An introduction to the issues of model quality and validation

7.2 Model quality concepts, model uncertainties and modelling errors

7.3 Model testing, verification and validation

7.4 Issues of model validation and model quality in typical applications

7.5 Issues of model quality in model reduction

7.6 Discussion

Chapter 8: Real-time simulation, virtual prototyping and partial-system testing


8.1 Virtual prototyping through simulation

8.2 Real-time simulation methods

8.3 Hardware-in-the-loop simulation

8.4 Multi-rate simulation techniques

8.5 Some new developments in real-time simulation

Chapter 9: Model management


9.1 Issues of model management

9.2 Tools for model management

9.3 Multi-formalism in simulation and modelling

9.4 Generic models

9.5 Validation of library sub-models and generic models

9.6 Educational issues

Chapter 10: Further discussion


10.1 A summary of some strategic issues in the modelling and simulation of integrated systems

10.2 Research and development work on modelling and simulation methods for integrated system applications

Appendix A1: models of an unmanned underwater vehicle (UUV)

Appendix A2: numerical methods for the solution of ordinary differential equations


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Murray-Smith, D JProfessor David J. Murray-Smith is Emeritus Professor and Honorary Senior Research Fellow at the School of Engineering at the University of Glasgow. He is also Adjunct Research Professor at California State University Chico. His research has involved helicopter flight mechanics model validation and system identification from flight data, flight control system design, ship and underwater vehicle control and collaborative work in other multidisciplinary areas such as hydro-turbine system modelling and control, electro-optic sensor systems and biomedical engineering.
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