Introduction |
9 |
Chapter 1 - Hybrid systems |
15 |
1.1 Hybrid system definitions, p. 15 - 1.2 Hybrid architectures, p. 18 |
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Chapter 2 - Hybrid systems modeling approaches |
21 |
2.1 Automata and transition systems, p. 23 - 2.2 Dynamical systems, p. 34 - 2.3 - Algebraic structures, p. 38 - 2.4 Programming languages, p. 39 - 2.5 Hybrid Petri nets, p. 41 - 2.6 Discrete abstractions, p. 45 - 2.7 Other techniques/theories, p. 53 - 2.8 Evaluation of the presented approaches, p. 58 |
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Chapter 3 - Autoregressive Conditional Duration models |
63 |
3.1 An introduction to the Autoregressive Conditional Duration models, p. 63 3.2 General structure of the ACD specification, p. 65 - 3.3 Linear ACD models, p. 66 - 3.4 Non-linear ACD models, p. 70 |
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Chapter 4 - The case study context |
75 |
4.1 The studied production system, p. 75 - 4.2 The studied production context as a hybrid system, p. 79 |
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Chapter 5 - The need of a new modeling approach |
83 |
5.1 Hybrid attributed Petri nets, p. 83 - 5.2 MR2002 modeling approach, p. 94 5.3 The need of a new modeling approach, p. 105 |
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Chapter 6 - The new approach for the logical modeling of hybrid production systems |
109 |
6.1 The proposed modeling method, p. 109 - 6.2 The application of the new approach, p. 112 - 6.3 Simulation model of the "furnace and spooling-bushing department" system, p. 118 |
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Chapter 7 - Results of the statistical analysis and concluding remarks |
135 |
7.1 Experimental campaign and statistical analysis of the outputs, p. 135 7.2 - Conclusions and further research, p. 139 |
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Appendix a |
145 |
Dynamical systems and automata, p. 145 - Hybrid Petri nets, p. 147 |
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Appendix b |
155 |
References |
165 |
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