Modelling and simulation of integrated systems in engineering issues of methodology, quality, testing and applications
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 en...
| Autor principal: | |
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| Formato: | Libro electrónico |
| Idioma: | Inglés |
| Publicado: |
Philadelphia, Pa. :
Woodhead Pub
2012.
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| Edición: | 1st edition |
| Materias: | |
| Ver en Biblioteca Universitat Ramon Llull: | https://discovery.url.edu/permalink/34CSUC_URL/1im36ta/alma991009628497106719 |
Tabla de Contenidos:
- Cover; Modelling and simulation of integrated systems in engineering: Issues of methodology, quality, testing and application; Copyright; Contents; List of figures; List of tables; List of abbreviations; Acknowledgements; Copyright acknowledgements; Product and trademark acknowledgements; Preface; About the author; 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 process1.7 References; 2 Integrated systems and their significance for system modelling; 2.1 An introduction to integrated systems; 2.2 Sequential and concurrent design procedures; 2.3 References; 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; 3.7 References
- 4 Inverse simulation for system modelling and design4.1 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; 4.6 References; 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 models5.5 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; 5.8 References; 6 Experimental modelling: system identification, parameter estimation and model optimisation techniques; 6.1 The use of system identifi cation 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 models6.3 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; 6.8 References
- 7 Issues of model quality and the validation of dynamic models
