Sensor Effects in Sliding Mode Control of Power Conversion Cells

Kafanas, Georgios

doi:10.1007/978-3-319-55642-0_20

Search citation statements

Order By: Relevance

Paper Sections

Select...

Examples1

Citation Types

Supporting

Mentioning

Contrasting

Year Published

2017

2018

Publication Types

Select...

Book2

Relationship

Self Cite0

Independent2

Authors

Journals

Cited by 2 publications

(1 citation statement)

References 1 publication

Supporting

Mentioning

Contrasting

Order By: Relevance

“…in terms of a constant matrix A and vector b describing electronic components. In [2] it is noted that, although a control system implements control on the state x, it does so by measuring not x itself, but a sensor value y, hence a more faithful model is (23)ẋ = Ax + bu ,ẏ = (x − y).κ , where u = step(y 1 − θ) ,…”

Section: Examplesmentioning

confidence: 99%

Regularization by External Variables

Bossolini

Edwards

Glendinning

et al. 2017

Trends in Mathematics

View full text Add to dashboard Cite

Regularization was a big topic at the 2016 CRM Intensive Research Program on Advances in Nonsmooth Dynamics. There are many open questions concerning well known kinds of regularization (e.g. by smoothing or hysteresis). Here we propose a framework for an alternative and important kind of regularization: by external variables. Shadowing in one variable Begin with a one-dimensional dynamical system (1)ẋ = −λ + xb(x; λ) where λ = sign(x). with the sign function being ±1 for x ≷ 0 and having the set value (−1, +1) for x = 0. This has an attracting fixed point on the discontinuity, whereẋ = −λ. Define a switch-shadowing system (2)ẋ = −λ + xb(x; λ) ,ẏ = (x − y)/γ , where λ = sign(y) , or a state-shadowing system (3)ẋ = −λ + yb(y; λ) ,ẏ = (x − y)/γ , where λ = sign(x) ,

show abstract

Section: Examplesmentioning

confidence: 99%