Observability is a measure of how well internal states of a system can be inferred from knowledge of its external outputs. Photo: CC-BY-2.0 Tim Rechmann (https://flic.kr/p/2kvnyb3) @phrawzty // Datadog
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Slide 6
Measure
Photo: CC-BY-2.0 Andrew Malone (https://flic.kr/p/aqhCH8) @phrawzty // Datadog
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Slide 7
State
Photo: CC-BY-2.0 BenGrantham (https://flic.kr/p/eQA3Zk) @phrawzty // Datadog
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Slide 8
System
Photo: CC-BY-2.0 Krzysztof Pędrys (https://flic.kr/p/4tUNYV) @phrawzty // Datadog
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Slide 9
Knowledge
Photo: CC-BY-2.0 Fredrik Rubensson (https://flic.kr/p/dC1gvd) @phrawzty // Datadog
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Slide 10
Output
Photo: CC-BY-2.0 Rob Brewer (https://flic.kr/p/VXgQqu) @phrawzty // Datadog
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Slide 11
Context is important (…and control theory is vast)
Photo: CC-BY-SA dilettantiquity (https://flic.kr/p/ppsKuz) @phrawzty // Datadog
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Slide 12
State observer
Photo: CC-BY-SA John Dyhouse (https://flic.kr/p/7ErCMc) @phrawzty // Datadog
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Slide 13
Multi & Bounding observer Interval & Luenberger observers Positive systems! Moving horizon estimations! Kalman filters in general topological spaces! Photo: CC-BY-SA https://en.wikipedia.org/wiki/State_observer @phrawzty // Datadog
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Slide 14
“The Three Pillars”
Photo: CC-BY-2.0 Andrew (https://flic.kr/p/xy6rdF) @phrawzty // Datadog
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Ok, so,
practically-speaking,
what is observability?! Photo: CC-BY-2.0 Becks (https://flic.kr/p/p1dHTN) @phrawzty // Datadog
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Slide 19
Observer / observed relationship Photo: CC-BY-SA Matt Brown (https://flic.kr/p/2hwn1DV) @phrawzty // Datadog
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Slide 20
Observability as a property of a system is important—but so is the observer’s capacity to make use of that property. Photo: Public Domain fdctsevilla (https://flic.kr/p/23rPAvU) @phrawzty // Datadog
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