Introduction 
9 
Chapter 1  Hybrid systems 
15 
1.1 Hybrid system definitions, p. 15  1.2 Hybrid architectures, p. 18 

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 

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 Nonlinear ACD models, p. 70 

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 



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 

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 spoolingbushing department" system, p. 118 

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 

Appendix a 
145 
Dynamical systems and automata, p. 145  Hybrid Petri nets, p. 147 

Appendix b 
155 
References 
165 
