lecture1 - ME/SE/EC 734 Hybrid systems theory computation...

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ME/SE/EC 734 Hybrid systems: theory, computation, and applications Fall 2013
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Instructor: Calin Belta 110 Cummington Mall, Room 414 Tel: 617 353 9586 Email: [email protected] Time and location: Mon & Wed 10:00 – 12:00, COM 210 Hybrid systems: theory, computation, and applications
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Grading: Homework (40%) & Project (60%) Textbook : none required. Class website : Blackboard, linked from hyness.bu.edu/calin Hybrid systems: theory, computation, and applications
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Course outline 1. Introduction, motivation, and examples 2. Models of hybrid systems (syntax) 3. Trajectories of hybrid systems (semantics) 4. Numerical simulation of hybrid systems 5. Stability of hybrid systems 6. Formal analysis and control of dynamical systems a) Transition systems, simulations, and bisimulations b) Propositional logics and first order logics c) Temporal logics and model checking d) Analysis and control for finite systems e) Analysis and control for continuous-time dynamical systems f) Analysis and control for discrete-time dynamical systems 7. Applications a) Symbolic motion planning and control b) Modeling and analysis of biochemical networks
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Course outline 1. Introduction, motivation, and examples 2. Models of hybrid systems (syntax) 3. Trajectories of hybrid systems (semantics) 4. Numerical simulation of hybrid systems 5. Stability of hybrid systems 6. Formal analysis and control of dynamical systems a) Transition systems, simulations, and bisimulations b) Propositional logics and first order logics c) Temporal logics and model checking d) Analysis and control for finite systems e) Analysis and control for continuous-time dynamical systems f) Analysis and control for discrete-time dynamical systems 7. Applications a) Symbolic motion planning and control b) Modeling and analysis of biochemical networks
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Introduction, motivation, and examples Hybrid systems are systems combining continuous and discrete dynamics. What are hybrid systems? (HSCC 2013): Hybrid systems research involves a blend of concepts, tools, and techniques from computer science, control theory, and applied mathematics for analysis and control of dynamical systems that exhibit continuous, discrete, or combined (hybrid) dynamics. By drawing on strategies from both computation and control, this field offers techniques applicable to both man-made, cyber-physical systems (ranging from mixed signal circuits and small robots to global infrastructure networks) and natural systems (ranging from biochemical networks to physiological models).
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Example: bouncing ball Introduction, motivation, and examples Processes with time-scale separation
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Example: bouncing ball Introduction, motivation, and examples
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  • Fall '13
  • Calin Belta
  • Logic, hybrid systems

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