Name
Abstract | ||
|---|---|---|
We consider a class of hybrid systems that involve random phenomena, in addition to discrete and continuous behaviour. Examples of such systems include wireless sensing and control applications. We propose and compare two abstraction techniques for this class of models, which yield lower and upper bounds on the optimal probability of reaching a particular class of states. We also demonstrate the applicability of these abstraction techniques to the computation of long-run average reward properties and the synthesis of controllers. The first of the two abstractions yields more precise information, while the second is easier to construct. For the latter, we demonstrate how existing solvers for hybrid systems can be leveraged to perform the computation. |
Year | DOI | Venue |
|---|---|---|
2011 | 10.1109/QEST.2011.17 | QEST |
Keywords | Field | DocType |
control application,particular class,optimal probability,existing solvers,long-run average reward property,hybrid system,probabilistic hybrid systems,abstractions yield,precise information,continuous behaviour,game-based abstraction,abstraction technique,controller synthesis,random processes,stochastic processes,stochastic process,game theory,upper bound,semantics,games,probabilistic logic,concrete,automata | Discrete mathematics,Control theory,Abstraction,Upper and lower bounds,Computer science,Automaton,Stochastic process,Theoretical computer science,Probabilistic logic,Hybrid system,Computation | Conference |
Citations | PageRank | References |
11 | 0.54 | 20 |
Authors | ||
5 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Ernst Moritz Hahn | 1 | 368 | 23.99 |
| Gethin Norman | 2 | 4163 | 193.68 |
| David Parker | 3 | 4018 | 184.00 |
| Bjorn Wachter | 4 | 28 | 1.36 |
| Lijun Zhang | 5 | 451 | 24.40 |