In this paper, we present a novel type of extremumseeking controller, which continuously uses past data of the performance map to estimate the gradient of this performance map by means of a 1st-order least squares fit. The approach is intuitive by nature and avoids the need of dither in the extremum-seeking loop. The avoidance of dither allows for an asymptotic stability result (opposed to practical stability in dither-based schemes) and, hence, for exact convergence to the performance optimal parameter. Additionally, the absence of dither eliminates one of the time-scales of classical extremumseeking schemes, allowing for a possibly faster convergence. A stability proof is presented for the static-map setting which relies on a Lyapunov-Razumikhin type of proof for time-delay systems. Simulations illustrate the effectiveness of the approach also for the dynamic setting. 53rd IEEE Conference on Decision and Control

In this paper, we introduce a variable-gain control strategy for mechanical ventilators in the respiratory systems. Respiratory systems assist the patients who have difficulty breathing on their own. For the comfort of the patient, fast pressure buildup (and release) and a stable flow response are desired. However, linear controllers typically need to balance between these conflicting objectives. In order to balance this tradeoff in a more desirable manner, a variable-gain controller is proposed, which switches the controller gain based on the magnitude of the patient flow. The effectiveness of the control strategy is demonstrated in experiments on different test lungs.

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DOI to the publisher's website.• The final author version and the galley proof are versions of the publication after peer review.• The final published version features the final layout of the paper including the volume, issue and page numbers. Link to publication General rightsCopyright and moral rights for the publications made accessible in the public portal are retained by the authors and/or other copyright owners and it is a condition of accessing publications that users recognise and abide by the legal requirements associated with these rights.• Users may download and print one copy of any publication from the public portal for the purpose of private study or research. • You may not further distribute the material or use it for any profit-making activity or commercial gain • You may freely distribute the URL identifying the publication in the public portal.If the publication is distributed under the terms of Article 25fa of the Dutch Copyright Act, indicated by the "Taverne" license above, please follow below link for the End User Agreement:

To deal with performance trade-offs in the control of motion systems, a method is developed for designing variablegain feedback controllers. The idea is to select a piecewise affine controller structure and, subsequently, to find the nonlinear controller parameter values of this structure by data-driven performance optimization. Herein an H2 performance objective is minimized. As a result, variable-gain controllers are synthesized using techniques from the field of learning and optimization. The method is applied to a wafer stage simulation model.

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