Rewarding probabilistic hybrid automata

2013 ◽  
Author(s):  
Ernst Moritz Hahn ◽  
Holger Hermanns
Keyword(s):  
Hybrid Automata

On the Issue of Stability of Hybrid Automata by a Part of Variables

2019 ◽  
Vol 51 (10) ◽  
pp. 23-30
Author(s):  
Alexey S. Bychkov ◽  
Olga N. Suprun ◽  
Irzhy Krzhyzh ◽  
Veronika Navotna
Keyword(s):  
Hybrid Automata

On complexity reduction of the discrete-event subsystem of Flat Hybrid Automata for control design

2020 ◽  
Vol 68 (7) ◽  
pp. 529-540
Author(s):  
Tobias Kleinert ◽  
Frederik Zahn ◽  
Veit Hagenmeyer
Keyword(s):  
Heuristic Algorithm ◽  
Adjacency Matrix ◽  
Discrete Event ◽  
Control Design ◽  
Differential Flatness ◽  
Hybrid Automata ◽  
Connected Automaton ◽  
Strongly Connected ◽  
Design Perspective ◽  
Technical Systems

AbstractThe class of hybrid systems describes most technical systems in great detail. However, the respective models and their behavior tend to be very complex. Recently, a new subclass of hybrid automata has been introduced, the Flat Hybrid Automata (FHA) that relies on the concepts of differential flatness for the continuous parts, and strongly connected automaton graphs for the discrete event part, in order to deal with the complexity from a design perspective. Therefore, we introduce in the present paper an approach to reduce the automaton graph of an FHA in a systematic way by removing edges from the adjacency matrix. The main contribution of the paper is twofold: Firstly, based on practical considerations we develop a heuristic algorithm to reduce the automaton graph. Secondly, we present possible ways to include knowledge about the system in the reduction.

Controlling chemical dosing for sulfide mitigation in sewer networks using a hybrid automata control strategy

2013 ◽  
Vol 68 (12) ◽  
pp. 2584-2590 ◽  
Author(s):  
Yiqi Liu ◽  
Ramon Ganigué ◽  
Keshab Sharma ◽  
Zhiguo Yuan
Keyword(s):  
Control Strategy ◽  
Control Method ◽  
Biological Processes ◽  
Control Performance ◽  
Hybrid Automata ◽  
Sewer Pipe ◽  
Physical Chemical ◽  
Iron Salts ◽  
Pumping Stations ◽  
Sewer Networks

Chemicals such as magnesium hydroxide (Mg(OH)2) and iron salts are widely used to control sulfide-induced corrosion in sewer networks composed of interconnected sewer pipe lines and pumping stations. Chemical dosing control is usually non-automatic and based on experience, thus often resulting in sewage reaching the discharge point receiving inadequate or even no chemical dosing. Moreover, intermittent operation of pumping stations makes traditional control theory inadequate. A hybrid automata-based (HA-based) control method is proposed in this paper to coordinate sewage pumping station operations by considering their states, thereby ensuring suitable chemical concentrations in the network discharge. The performance of the proposed control method was validated through a simulation study of a real sewer network using real sewage flow data. The physical, chemical and biological processes were simulated using the well-established SeweX model. The results suggested that the HA-based control strategy significantly improved chemical dosing control performance and sulfide mitigation in sewer networks, compared to the current common practice.

Monitoring of dynamic processes by rectangular hybrid automata

2010 ◽  
Vol 4 (4) ◽  
pp. 766-774 ◽  
Author(s):  
Mohamed Fathi Karoui ◽  
Hassane Alla ◽  
Abderrazak Chatti
Keyword(s):  
Dynamic Processes ◽  
Hybrid Automata

scholarly journals Exact and fully symbolic verification of linear hybrid automata with large discrete state spaces

2012 ◽  
Vol 77 (10-11) ◽  
pp. 1122-1150 ◽  
Author(s):  
Werner Damm ◽  
Henning Dierks ◽  
Stefan Disch ◽  
Willem Hagemann ◽  
Florian Pigorsch ◽  
...  
Keyword(s):  
Hybrid Automata ◽  
State Spaces ◽  
Discrete State ◽  
Linear Hybrid Automata ◽  
Symbolic Verification

Quantitative Models for Complex Physical Systems

2014 ◽  
Vol 1061-1062 ◽  
pp. 1144-1147
Author(s):  
Jun Fu ◽  
Jin Zhao Wu ◽  
Ning Zhou ◽  
Hong Yan Tan
Keyword(s):  
Quantitative Analysis ◽  
State Space ◽  
Control Systems ◽  
Chemical Reaction ◽  
Metric Space ◽  
Manufacturing Systems ◽  
Quantitative Model ◽  
Hybrid Automata ◽  
Physical Systems ◽  
The Difference

We present a quantitative model, called metric hybrid automata, for quantifying the behaviors of complex physical systems, such as chemical reaction control systems, manufacturing systems etc. Due to the introduction of a metric, the state space of hybrid automata forms a metric space, in which the difference of states can be quantified. Furthermore, in order to reveal the distance of system behaviors, we construct the simulation distance and the bisimulation distance, which quantify the similarity of system behaviors. Our model provides the basis for quantitative analysis for those complex physical systems.

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