Optimal observation mode scheduling for systems under temporal constraints
| Autor: | Eva Tesarova, Jiri Barnat, Ivana Černá, Maria Svorenova |
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| Rok vydání: | 2016 |
| Předmět: |
FOS: Computer and information sciences
0209 industrial biotechnology Mathematical optimization Computer Science - Logic in Computer Science Computer science Systems and Control (eess.SY) 02 engineering and technology Optimal control Logic in Computer Science (cs.LO) Scheduling (computing) 020901 industrial engineering & automation Computer Science - Computer Science and Game Theory Control system Bounded function FOS: Electrical engineering electronic engineering information engineering 0202 electrical engineering electronic engineering information engineering Computer Science - Systems and Control 020201 artificial intelligence & image processing Computer Science and Game Theory (cs.GT) |
| Zdroj: | ACC |
| ISSN: | 2378-5861 |
| Popis: | Autonomous control systems use various sensors to decrease the amount of uncertainty under which they operate. While providing partial observation of the current state of the system, sensors require resources such as energy, time and communication. We consider discrete systems with non-deterministic transitions and multiple observation modes. The observation modes provide different information about the states of the system and are associated with non-negative costs. We consider two control problems. First, we aim to construct a control and observation mode switching strategy that guarantees satisfaction of a finite-time temporal property given as a formula of syntactically co-safe fragment of LTL (scLTL) and at the same time, minimizes the worst-case cost accumulated until the point of satisfaction. Second, the bounded version of the problem is considered, where the temporal property must be satisfied within given finite time bound. We present correct and optimal solutions to both problems and demonstrate their usability on a case study motivated by robotic applications. Technical report accompanying ACC'16 paper |
| Databáze: | OpenAIRE |
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