This item is in: Engineering > Mechanical engineering and general materials
Modelling and simulation of integrated systems in engineering: Issues of methodology, quality, testing and applicationD J Murray-Smith, University of Glasgow, UK
- 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
- particular attention is given to integrated systems applications involving complex design processes where decisions involving one sub-system have a direct bearing on the design of other sub-systems and on the overall structure of the complete system
- issues of model documentation, version control and the use of generic models are carefully considered
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.
ISBN 0 85709 078 X
ISBN-13: 978 0 85709 078 2
May 2012
372 pages 234 x 156mm hardback
£145.00 / US$245.00 / €175.00
Usually dispatched within 24 hours
About the author
Professor 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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Contents
The principles of system modelling
- General issues in the development and application of models
- Classes of model for engineering applications
- Questions of model quality
- Methods of experimental modelling
- Model reuse and generic models
- Modelling within the procurement process
- References
Integrated systems and their significance for system modelling
- An introduction to integrated systems
- Sequential and concurrent design procedures
- References
Problem organisation
- Model organisation for engineering systems design
- The physical component layer
- The physical concept layer
- The mathematical description layer
- Software for modelling and simulation
- New developments in the modelling and simulation of micro- and nano-mechanical systems
- References
Inverse simulation for system modelling and design
- An introduction to inverse modelling and inverse simulation
- Methods of inverse simulation
- Example: inverse simulation applied to a linear model
- Case study: an application involving a nonlinear unmanned underwater vehicle (UUV) system model
- Discussion
- References
Methods and applications of parameter sensitivity analysis
- Fundamental concepts of parameter sensitivity analysis
- The sensitivity function
- Methods of sensitivity analysis involving repeated solutions
- Methods of sensitivity analysis involving sensitivity models
- Case study: sensitivity analysis applied to the unmanned underwater vehicle (UUV) model
- Sensitivity analysis using bond graphs
- Sensitivity analysis in inverse simulation
- References
Experimental modelling: system identification, parameter estimation and model optimisation techniques
- The use of system identifi cation and optimisation
- techniques in the development of physically based dynamic models
- Applications of conventional methods of system identification and parameter estimation to physically based models
- System identification and parameter estimation applied to helicopter fl ight mechanics models
- Some selected methods of local and global parameter optimisation
- Genetic programming (GP) for model structure estimation
- Some practical issues in global parameter optimisation
- Further examples of system identifi cation, parameter estimation and model optimisation techniques in integrated systems applications
- References
Issues of model quality and the validation of dynamic models
- An introduction to the issues of model quality and validation
- Model quality concepts, model uncertainties and modelling errors
- Model testing, verifi cation and validation
- Issues of model validation and model quality in typical applications
- Issues of model quality in model reduction
- Discussion
- References
Real-time simulation, virtual prototyping and partial-system testing
- Virtual prototyping through simulation
- Real-time simulation methods
- Hardware-in-the-loop simulation
- Multi-rate simulation techniques
- Some new developments in real-time simulation
- References
Model management
- Issues of model management
- Tools for model management
- Multi-formalism in simulation and modelling
- Generic models
- Validation of library sub-models and generic models
- Educational issues
- References
Further discussion
- A summary of some strategic issues in the modelling and simulation of integrated systems
- Research and development work on modelling and simulation methods for integrated system applications
Modelling integrated engineering systems: Appendix A1 – Models of an unmanned underwater vehicle (UUV)
Modelling integrated engineering systems: Appendix A2 – Numerical methods for the solution of ordinary differential equations