Robust control design method for uncertain system using a set of measurements

Khadraoui, Sofiane; Nounou, Hazem; Nounou, Mohamed; Datta, Aniruddha; Bhattacharyya, S.P.

doi:10.1109/acc.2013.6580505

Cited by 7 publications

(6 citation statements)

References 23 publications

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“…This results in the model matching problem ∀p ∈ P (7) which is a second order cone optimization problem that is convex in θ. Note that in general, the optimization problem posed in (7) is not equivalent to (6). If there exists a θ such that T p (e iω , θ) = M (e iω ) ∀p ∈ P, then (7) and (6) are equivalent.…”

Section: A Controller Parametrizationmentioning

confidence: 99%

Towards Data-Driven LPV Controller Synthesis Based on Frequency Response Functions

Bloemers

Tóth

Oomen

2019

2019 IEEE 58th Conference on Decision and Control (CDC)

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Section: A Controller Parametrizationmentioning

confidence: 99%

Towards Data-Driven LPV Controller Synthesis Based on Frequency Response Functions

Bloemers

Tóth

Oomen

2019

2019 IEEE 58th Conference on Decision and Control (CDC)

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“…Another frequency‐domain approach is presented in to design reduced order controllers with a guaranteed bounded error on the difference between the desired and achieved magnitude of closed‐loop sensitivity functions; this approach also uses a non‐convex optimization method. An interval‐based optimization method is used to compute fixed‐order robust controller using the uncertain frequency‐response of the system in . However, the optimization method is not convex and the resulting controller does not guarantee the closed‐loop stability (which should be verified a posteriori).…”

Section: Introductionmentioning

confidence: 99%

Robust H_∞ controller design using frequency‐domain data via convex optimization

Karimi

Nicoletti

Zhu

2016

Intl J Robust & Nonlinear

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SUMMARYA new robust controller design method that satisfies the H∞ criterion is developed for linear timeinvariant single-input single-output (SISO) systems. A data-driven approach is implemented in order to avoid the unmodeled dynamics associated with parametric models. This data-driven method uses fixed order controllers to satisfy the H∞ criterion in the frequency domain. The necessary and sufficient conditions for the existence of such controllers are presented by a set of convex constraints. These conditions are also extended to systems with frequency-domain uncertainties in polytopic form. It is shown that the upper bound on the weighted infinity norm of the sensitivity function converges monotonically to the optimal value, when the controller order increases. Additionally, the practical issues involved in computing fixed-order rational H∞ controllers in discrete-or continuous-time by convex optimization techniques are addressed. Copyright

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“…The authors in [3] establish a robust frequencydomain controller design method that requires a solution to a non-linear optimization problem. A frequency-domain loopshaping method for fixed-structure controllers is proposed in [4]; however, stability is not guaranteed with this method and must be verified a posteriori.…”

Section: Introductionmentioning

confidence: 99%

A data-driven approach to power converter control via convex optimization

Nicoletti

Martino

Karimi

2017

2017 IEEE Conference on Control Technology and Applications (CCTA)

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Abstract-A new model reference data-driven approach is presented for synthesizing controllers for the CERN power converter control system. This method uses the frequency response function (FRF) of a system in order to avoid the problem of unmodeled dynamics associated with low-order parametric models. For this particular application, it is shown that a convex optimization problem can be formulated (in either the H∞ or H2 sense) to shape the closed-loop FRF while guaranteeing the closed-loop stability. This optimization problem is realized by linearizing a non-convex constraint around a stabilizing operating point. The effectiveness of the method is illustrated by designing a controller for the SATURN power converter which is used in the Large Hadron Collider, in injector machines, and for pulsed applications at CERN. Experimental validation in the frequency-domain is also presented.

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Robust control design method for uncertain system using a set of measurements

Cited by 7 publications

References 23 publications

Towards Data-Driven LPV Controller Synthesis Based on Frequency Response Functions

Towards Data-Driven LPV Controller Synthesis Based on Frequency Response Functions

Robust H_∞ controller design using frequency‐domain data via convex optimization

A data-driven approach to power converter control via convex optimization

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Robust control design method for uncertain system using a set of measurements

Cited by 7 publications

References 23 publications

Towards Data-Driven LPV Controller Synthesis Based on Frequency Response Functions

Towards Data-Driven LPV Controller Synthesis Based on Frequency Response Functions

Robust H∞ controller design using frequency‐domain data via convex optimization

A data-driven approach to power converter control via convex optimization

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Resources

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Robust H_∞ controller design using frequency‐domain data via convex optimization