Qualitative modelling of linear dynamical systems with quantized state measurements

Lunze, Jan

doi:10.1016/0005-1098(94)90119-8

Cited by 156 publications

(90 citation statements)

References 17 publications

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“…Finally, we would like to emphasize that the idea of using symbolic models for the control of continuous systems is not new and motivated much research in the area of hybrid systems [4], [12], [14], [24], [29], [32], [34], [40], [42], [47], [54]. Even though the use of symbolic models was advocated by these and many other researchers, the applicability of the proposed methods has always remained an open problem due to the lack of results ensuring existence of symbolic models for control systems.…”

Section: Related Workmentioning

confidence: 99%

Symbolic Control of Linear Systems Based on Symbolic Subsystems

Tabuada

2006

IEEE Trans. Automat. Contr.

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Abstract-This paper describes an approach to the control of continuous systems through the use of symbolic models describing the system behavior only at a finite number of points in the state space. These symbolic models can be seen as abstract representations of the continuous dynamics enabling the use of algorithmic controller design methods. We identify a class of linear control systems for which the loss of information incurred by working with symbolic subsystems can be compensated by feedback. We also show how to transform symbolic controllers designed for a symbolic subsystem into controllers for the original system. The resulting controllers combine symbolic controller dynamics with continuous feedback control laws and can thus be seen as hybrid systems. Furthermore, if the symbolic controller already accounts for software/hardware requirements, the hybrid controller is guaranteed to enforce the desired specifications by construction thereby reducing the need for formal verification.

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Section: Related Workmentioning

confidence: 99%

Symbolic Control of Linear Systems Based on Symbolic Subsystems

Tabuada

2006

IEEE Trans. Automat. Contr.

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“…Since the system under consideration has restriction on measurability of input and output, it can be considered as a " quantised system" whose structure is shown in Figure 2 (Lunze, 1994;Teneketzis et al, 1994). The system under consideration is the continuous-variable system described by (1).…”

Section: Determination Of Timed Automatamentioning

confidence: 99%

“…the system is equipped with discrete level sensors so signals from the system can only be measured qualitatively such as "low", "medium", and "high". Thus the system can be regarded as a "quantised system" as described by (Lunze, 1994;. This paper consists of two main parts.…”

Section: Introductionmentioning

confidence: 99%

Diagnosis of Discrete–event System Described by Timed Automata

Lunze

Supavatanakul

2002

IFAC Proceedings Volumes

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This paper presents the model-based diagnosis in the framework of discrete-event systems. Timed automata are used as a discrete-event representation which is suitable for consistency-based diagnosis. The diagnostic statement is based on the observation whether the measured event-time sequences are consistent with the timed automata. The diagnostic algorithm can be applied online because it determines the fault occurrence recursively for the measured event-time sequences. The result is applied to diagnose valve faults in a chemical process.

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“…In this work, a new approach based on a qualitative modelling technique is presented that is suitable for a variety of network-intensive software utilities and for its use to predict the QoS within geographically distributed multi-cloud environments. Qualitative modelling is a well-known technique [31], used mostly in control and analysis of complex systems. It is resilient to noise, requires small learning sets and is more intuitive for human understanding than most other Machine Learning systems.…”

Section: Introductionmentioning

confidence: 99%

QoS-Aware Orchestration of Network Intensive Software Utilities within Software Defined Data Centres

et al. 2017

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Although the cloud computing domain is progressing rapidly, the deployment of various network intensive software utilities in the cloud is still a challenging task. The Quality of Service (QoS) for various gaming, simulations, video-conferencing, video-streaming or even file uploading tasks may be significantly affected by the quality and geolocation of the selected underlying computing resources, which are available only when the specific functionality is required. This study presents a new architecture for geographic orchestration of network intensive software components which is designed for high QoS. Key elements of this architecture are a Global Cluster Manager (GCM) operating within Software Defined Data Centres (SDDCs), a runtime QoS Monitoring System, and a QoS Modeller and Decision Maker for automated orchestration of software utilities. The implemented system automatically selects the best geographically available computing resource within the SDDC according to the developed QoS model of the software component. This architecture is event-driven as the services are deployed and destroyed in real-time for every usage event. The utility of the implemented orchestration technology is verified qualitatively, and in relation to the potential gains of selected QoS metrics by using two network intensive software utilities implemented as containers: an HTTP(S) file upload service and a Jitsi Meet videoconferencing service. The study shows potential for QoS improvements in comparison to existing orchestration systems.

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Qualitative modelling of linear dynamical systems with quantized state measurements

Cited by 156 publications

References 17 publications

Symbolic Control of Linear Systems Based on Symbolic Subsystems

Symbolic Control of Linear Systems Based on Symbolic Subsystems

Diagnosis of Discrete–event System Described by Timed Automata

QoS-Aware Orchestration of Network Intensive Software Utilities within Software Defined Data Centres

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