T1 - Revision history

Faber at 09:37, 29 June 2016

2016-06-29T09:37:08Z

Faber at 08:26, 14 June 2016

2016-06-14T08:26:49Z

Faber at 12:51, 13 June 2016

2016-06-13T12:51:47Z

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 '''Intended Audience:''' Students and researchers interested in the topic of state estimation and control in distributed and networked systems with limited hardware resources.
-'''Description:''' How can we achieve high performance on embedded platforms with limited computing and communication resources? This question represents a key challenge in intelligent systems research, for example, when high-performance control must run on low-power computing hardware, or multiple agents share a wireless communication network. Traditional periodic sampling methods are inherently limited: data is processed or transmitted at a-priori fixed time instants, irrespective of whether there is any need for an update or control action, or not. The event-based sampling paradigm, which has received a lot of attention recently in controls and signal processing, addresses this limitation by performing computation and communication only when necessary as indicated by system-inherent events (for example, an error passing a threshold level, or estimation uncertainty growing too large). With event-based methods, average usage of resources can significantly be reduced compared to traditional periodic designs. Hence, event-based methods allow the designer to achieve high system performance with reduced resource usage.
+'''Description:''' How can we achieve high performance on embedded platforms with limited computing and communication resources? This question represents a key challenge in intelligent systems research, for example, when high-performance control must run on low-power computing hardware, or multiple agents share a wireless communication network. Traditional periodic sampling methods are inherently limited: data is processed or transmitted at a-priori fixed time instants, irrespective of whether there is any need for an update or control action, or not. The event-based sampling paradigm, which has received a lot of attention recently in controls and signal processing, addresses this limitation by performing computation and communication only when necessary as indicated by system-inherent events (for example, an error passing a threshold level, or estimation uncertainty growing too large). With event-based methods, average usage of resources can significantly be reduced compared to traditional periodic designs. Hence, event-based methods allow the designer to achieve high system performance with reduced resource usage.<br />
 This tutorial will provide an introduction to the problem of event-based state estimation (and control). In particular, we shall consider a scenario where multiple distributed agents observe a dynamic process and share sensory data over a network in order to solve a joint state estimation and sensor fusion problem. We review recent developments in the area and highlight important theoretical and technical challenges. In particular, we discuss the key aspects of event-based system design: (i) the design of event-triggering mechanisms, (ii) (sub-)
 optimal estimation and filtering algorithms, and (iii) distributed architectures. In addition to

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 '''Length:''' 3 hours
-'''Intended Audience:'''
+'''Intended Audience:''' Students and researchers interested in the topic of state estimation and control in distributed and networked systems with limited hardware resources.
-'''Description:'''
+'''Description:''' How can we achieve high performance on embedded platforms with limited computing and communication resources? This question represents a key challenge in intelligent systems research, for example, when high-performance control must run on low-power computing hardware, or multiple agents share a wireless communication network. Traditional periodic sampling methods are inherently limited: data is processed or transmitted at a-priori fixed time instants, irrespective of whether there is any need for an update or control action, or not. The event-based sampling paradigm, which has received a lot of attention recently in controls and signal processing, addresses this limitation by performing computation and communication only when necessary as indicated by system-inherent events (for example, an error passing a threshold level, or estimation uncertainty growing too large). With event-based methods, average usage of resources can significantly be reduced compared to traditional periodic designs. Hence, event-based methods allow the designer to achieve high system performance with reduced resource usage.
-'''Prerequisites:'''
+'''Prerequisites:''' Basic knowledge in mathematics (probability, linear algebra), dynamic systems (linear systems),
 '''Presenter:''' [mailto:strimpe@tuebingen.mpg.de Sebastian Trimpe]
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