Searched for: author%3A%22Aarnoudse%2C+Leontine%22
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Aarnoudse, Leontine (author), Kon, Johan (author), Ohnishi, Wataru (author), Poot, Maurice (author), Tacx, Paul (author), Strijbosch, Nard (author), Oomen, T.A.E. (author)
The performance of feedforward control depends strongly on its ability to compensate for reproducible disturbances. The aim of this paper is to develop a systematic framework for artificial neural networks (ANN) for feedforward control. The method involves three aspects: a new criterion that emphasizes the closed-loop control objective,...
journal article 2024
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Aarnoudse, Leontine (author), Kon, Johan (author), Classens, Koen (author), van Meer, Max (author), Poot, Maurice (author), Tacx, Paul (author), Strijbosch, Nard (author), Oomen, T.A.E. (author)
Cross-coupled iterative learning control (ILC) can improve the contour tracking performance of manufacturing systems significantly. This paper aims to develop a framework for norm-optimal cross-coupled ILC that enables intuitive tuning of time- and iteration-varying weights of the exact contour error and its tangential counterpart. This leads...
journal article 2024
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Aarnoudse, Leontine (author), Cox, Kevin (author), Koekebakker, Sjirk (author), Oomen, T.A.E. (author)
The increasing complexity of next-generation mechatronic systems leads to different types of periodic disturbances, which require dedicated repetitive control strategies to attenuate. The aim of this paper is to develop a new repetitive control strategy to completely attenuate a periodic disturbance and a user-defined number of relevant...
journal article 2024
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Aarnoudse, Leontine (author), Pavlov, Alexey (author), Oomen, T.A.E. (author)
Iterative learning control (ILC) and repetitive control (RC) can lead to high performance by attenuating repeating disturbances perfectly, yet these approaches may amplify non-repeating disturbances. The aim of this paper is to achieve both perfect, fast attenuation of repeating disturbances and limited amplification of non-repeating...
journal article 2024
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Aarnoudse, Leontine (author), Pavlov, Alexey (author), Kon, Johan (author), Oomen, T.A.E. (author)
Repetitive control can lead to high performance by attenuating periodic disturbances completely, yet it may amplify non-periodic disturbances. The aim of this paper is to achieve both fast learning and low errors in repetitive control. To this end, a nonlinear learning filter is introduced that distinguishes between periodic and non-periodic...
conference paper 2023
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Aarnoudse, Leontine (author), Pavlov, Alexey (author), Oomen, T.A.E. (author)
Iterative learning control (ILC) involves a trade-off between perfect, fast attenuation of iteration-invariant disturbances and amplification of iteration-varying ones. The aim of this paper is to develop a nonlinear ILC framework that achieves fast convergence, robustness, and low converged error values in ILC. To this end, the method...
journal article 2023
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Aarnoudse, Leontine (author), Oomen, T.A.E. (author)
Iterative feedback tuning (IFT) enables the tuning of feedback controllers based on measured data without the need for a parametric model. The aim of this paper is to develop an efficient method for MIMO IFT that reduces the required number of experiments. Using a randomization technique, an unbiased gradient estimate is obtained from a...
conference paper 2023
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Aarnoudse, Leontine (author), Strijbosch, Nard (author), Tacx, Paul (author), Verschueren, Edwin (author), Oomen, T.A.E. (author)
Piezo stepper actuators are very promising for nanopositioning systems due to their high resolution, high stiffness, fast response, and the ability to position a mover over an infinite stroke by means of motion reminiscent of walking. The aim of this paper is to enhance the waveforms for actuating piezo steppers, by actively compensating for...
journal article 2023
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Aarnoudse, Leontine (author), Kon, Johan (author), Classens, Koen (author), van Meer, Max (author), Poot, Maurice (author), Tacx, Paul (author), Strijbosch, Nard (author), Oomen, T.A.E. (author)
Cross-coupled iterative learning control (ILC) can achieve high performance for manufacturing applications in which tracking a contour is essential for the quality of a product. The aim of this paper is to develop a framework for norm-optimal cross-coupled ILC that enables the use of exact contour errors that are calculated offline, and...
conference paper 2022
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Aarnoudse, Leontine (author), Oomen, T.A.E. (author)
Parameterized feedforward control is at the basis of many successful control applications with varying references. The aim of this paper is to develop an efficient data-driven approach to learn the feedforward parameters for MIMO systems. To this end, a cost criterion is minimized using a stochastic gradient descent algorithm, in which both...
journal article 2022
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Aarnoudse, Leontine (author), Oomen, T.A.E. (author)
Data-driven iterative learning control can achieve high performance for systems performing repeating tasks without the need for modeling. The aim of this paper is to develop a fast data-driven method for iterative learning control that is suitable for massive MIMO systems through the use of efficient unbiased gradient estimates. A stochastic...
conference paper 2021
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