Youla-Kucera adaptive feedback disturbance rejection in the presence of plant uncertainties

Vau, Bernard; Landau, Ioan Doré

doi:10.1109/cdc40024.2019.9030073

Cited by 4 publications

(12 citation statements)

References 13 publications

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“…∞ . Consequently a sufficient stability condition for the closed-loop is (24). Now at the frequencies ω j , equation ( 14) must be So(e −iω j ) H R (e −iω j )H S (e −iω j )e −iω j do e −do iω j Bo(e −iω j ) , by combining with (24), one obtains condition (23).…”

Section: Discussionmentioning

confidence: 99%

“…80, 244, 400, 686, 828, 1110, and 1200 Hz. The inequality (24) suggests to design So(z −1 ) H R (z −1 ) as series of band-pass filters with a strong amplification at these frequencies. Additionally, H R incorporates zeros at −1 and +1, in order to open the loop at 0 Hz and 0.5/T s Hz.…”

Section: Test-bench Descriptionmentioning

confidence: 99%

“…48-49, to our knowledge this approach has never been worked in detail to establish a clear procedure and to provide stability conditions. Preliminary results have been presented in [24]. The paper is organized as follows: Section 2 gives the description of the basic control structure.…”

Section: Introductionmentioning

confidence: 99%

“…It was observed that augmenting the size of the Q filter leads to a reduction of Q(e −iω ) in the regions concerned by condition(24) …”

mentioning

confidence: 99%

See 3 more Smart Citations

Adaptive rejection of narrow-band disturbances in the presence of plant uncertainties—A dual Youla–Kucera approach

Vau¹,

Landau

2021

Automatica

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The stability of adaptive disturbance rejection schemes using Youla-Kucera (YK) parametrization and the internal model principle (IMP) in the presence of plant model uncertainties is investigated. The problem is approached by using the dual Youla Kucera parametrization for the description of the plant model uncertainties. The known disturbance case is discussed first, emphasizing the need of over parametrization of the Youla Kucera filter used for control in order to both solving the IMP and the stability problems. Then this solution is extended for the case of unknown disturbances leading to the use of a parameter adaptation algorithm with projection. A stability analysis of the adaptive scheme is provided. Simulation results on relevant examples and experimental evaluation on an active noise attenuation system illustrate the possibilities of this approach for handling significant plant-model mismatch.

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Section: Discussionmentioning

confidence: 99%

Section: Test-bench Descriptionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

“…It was observed that augmenting the size of the Q filter leads to a reduction of Q(e −iω ) in the regions concerned by condition(24) …”

mentioning

confidence: 99%

See 2 more Smart Citations

Adaptive rejection of narrow-band disturbances in the presence of plant uncertainties—A dual Youla–Kucera approach

Vau¹,

Landau

2021

Automatica

Self Cite

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“…However, this solution needs to satisfy stability conditions which cannot be fulfilled for all systems especially when the uncertainty is large. A recent work Vau and Landau (2019) showed that this difficulty can be overcome by increasing the order of the filter Q. This solution is called YK overparametrization.…”

Section: Discussionmentioning

confidence: 99%

Advances in Youla-Kucera parametrization: A Review

Mahtout

Navas

Milanés

et al. 2020

Annual Reviews in Control

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Youla-Kucera (YK) parametrization was formulated decades ago for obtaining the set of controllers stabilizing a linear plant. This fundamental result of control theory has been used to develop theoretical tools solving many control problems ranging from stable controller switching, closed-loop identification, robust control, disturbance rejection, adaptive control to fault tolerant control. This paper collects the recent work and classifies them according to the use of YK parametrization, Dual YK parametrization or both, providing the latest advances with main applications in different control fields. A final discussion gives some insights on the future trends in the field.

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Handling large model uncertainty in adaptive feedback noise attenuation by overparametrization

Buche

Vau²,

Landau

et al. 2021

Journal of Sound and Vibration

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Adaptive feedback noise attenuation is a very efficient way of strongly attenuating multiple tonal and narrow band disturbances with unknown and time varying characteristics. These adaptive schemes implement the internal model principle (IMP) for canceling disturbances combined with the Youla Kucera (YK) parametrization which allows to directly tune the disturbance compensation filter without explicit identification of the disturbance model. Efficient use of these schemes requires a good knowledge of the compensatory path model, which can be obtained by experimental system identification. However, there are potential applications where the characteristics of the compensatory path may change significantly during operation and this may lead to the instability of the system. The paper addresses the problem of handling large plant model uncertainties by overparametrization of the adaptive disturbance compensation filter. A methodology for designing adaptive feedback noise cancelers in the presence of large model uncertainties is proposed. In addition to the overparamtrization, a specific design of the linear feedback controller has to be done in order to satisfy a frequency condition in the range of variations of the frequencies characteristics of the compensatory path model. Experimental validation of the design is done on a relevant active noise control bench test.

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Youla-Kucera adaptive feedback disturbance rejection in the presence of plant uncertainties

Cited by 4 publications

References 13 publications

Adaptive rejection of narrow-band disturbances in the presence of plant uncertainties—A dual Youla–Kucera approach

Adaptive rejection of narrow-band disturbances in the presence of plant uncertainties—A dual Youla–Kucera approach

Advances in Youla-Kucera parametrization: A Review

Handling large model uncertainty in adaptive feedback noise attenuation by overparametrization

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