Special Issue "Real Time Dependable Distributed Control Systems"
Deadline for manuscript submissions: closed (15 September 2018)
Prof. Dr.-Ing. Sergio Montenegro
Informatik für Luft- und Raumfahrt, Universität Würzburg, 97074 Würzburg, Germany
Website | E-Mail
Phone: +49 931 / 31-83715
Interests: real time dependable distributed control systems; aerospace applications; real time operating systems; real time communication protocols and middleware; UAS/UAV Drones/unmanned areal vehicles and systems; AUVs Under Autonomous Underwater vehicles; satellites and space vehicles
If it (the machine) is truly dependable, it must be distributed! Do you agree? If not, you are invited to present your thesis or idea.
That is not all, however. Distributed control has another face: the distributed closed loop and/or feedback control.
The first face: Dependability implies distributed real-time control, because we must avoid any possible single points of global failure, including physical damages. Therefore, the functionality has to be redundant (e.g., replicated) and distributed in different physical locations (of the machine). This requires robust real-time communication links and protocols, which normally cannot guarantee the delivery of each and every message. This requires control algorithms which can operate correctly, even in the case of message loss. This implies predictors and mathematical models. Replication is not enough—we need redundancy management and correct state estimation despite inconsistent, contradictory, and/or missing data and measurements, and all of this in real-time.
The second face: We have cooperating independent agents with a common goal. The actions of each one must be coordinated with all others in real-time. These agents are distributed spatially, for example, and controlled by multiple individual controllers which are interconnected. The controllers exchange knowledge between each other and thus provide performance results similar to centralized control systems, while being more reliable (due to redundancy), easier to implement (e.g., if the subsystems are spatially distributed like satellites), and have lower communication requirements than a centralized control. On the other hand, controller design is much more demanding, since each individual controller also has to model some (or all) other agents, and state exchange between the controllers has to be implemented.
You are invited to contribute to or to contradict these theses.Prof. Dr. Sergio Montenegro
Manuscript Submission Information
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- Real-time communication protocols and middleware
- Redundancy and redundancy management
- Predictors and mathematical models
- Robust and fault-tolerant control/steering
- Real-time operating systems for distributed real-time control
- Distributed state estimation
- Distributed close loop / feedback control
- Model predictive control
- Robust control