10. Mixed logical dynamical (MLD) systems
Learning goals
B(E)3M35HYS – Hybrid systems
0. Introduction
What is a hybrid system?
Course outline
Literature
1. Discrete-event systems: Automata
Learning goals
Discrete-event systems
State automata
Software
Literature
2. Discrete-event systems: Petri nets
Learning goals
Petri nets
Timed Petri nets
Software
Literature
3. Discrete-event systems: Max-plus systems
Learning goals
Max-plus algebra
Max-plus linear (MPL) systems
Software
Literature
4. Hybrid systems: Hybrid automata
Learning goals
Hybrid automata
Software
Literature
5. Hybrid systems: Hybrid equations
Learning goals
Hybrid equations
Software
Literature
6. Some classes of hybrid systems
Learning goals
Reset systems
Switched systems
Piecewise affine (PWA) systems
Software
Literature
7. Solution
solution_goals.qmd
Solution concepts
Types of solutions
Literature
8. Stability
Learning goals
Recap of stability analysis for continuous dynamical systems
Stability of hybrid systems
Stability via common Lyapunov function
Stability via multiple Lyapunov functions
Software
Literature
9. Complementarity systems
Learning goals
Complementarity constraints
Complementarity systems
Simulations of complementarity systems using time-stepping
Software
Literature
10. Mixed logical dynamical (MLD) systems
Learning goals
Discrete hybrid automata
Logic vs inequalities
Components of DHA as inequalities
Mixed logical dynamical (MLD) systems
Software
Literature
11. Model predictive control (MPC) for MLD systems
Learning goals
Online MPC for hybrid systems
Explicit MPC for hybrid systems
Software
Literature
12. Formal verification
verification_goals.qmd
What is verification?
Reachability analysis
Barrier certificates
Temporal logics
Software
Literature
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Knowledge (remember and understand)
Skills (use the knowledge to solve a problem)
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10. Mixed logical dynamical (MLD) systems
Learning goals
Learning goals
Knowledge (remember and understand)
…
Skills (use the knowledge to solve a problem)
…
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Literature
Discrete hybrid automata