Results 31 to 40 of about 1,084,598 (183)
Direct Data-Driven State-Feedback Control of General Nonlinear Systems [PDF]
2023 62nd IEEE Conference on Decision and Control (CDC), 2023 Accepted for the 62nd IEEE Conference on Decision and Control (CDC2023)
Chris Verhoek +3 more
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Direct data-driven control of linear parameter-varying systems [PDF]
52nd IEEE Conference on Decision and Control, 2013 In many control applications, nonlinear plants can be modeled as linear parameter-varying (LPV) systems, by which the dynamic behavior is assumed to be linear, but also dependent on some measurable signals, e.g., operating conditions. When a measured data set is available, LPV model identification can provide low complexity linear models that can embed
Simone Formentin +3 more
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Direct data-driven control with signal temporal logic specifications [PDF]
IFAC-PapersOnLine, 2023 Most control synthesis methods under temporal logic properties require a model of the system, however, identifying such a model can be a challenging task. In this work, we develop a direct data-driven control synthesis method for temporal logic specifications, which does not require this explicit modeling step, capable of providing certificates for the
B. C. van Huijgevoort +3 more
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Set-Theoretic Direct Data-driven Predictive Control
2025 European Control Conference (ECC)Designing the terminal ingredients of direct data-driven predictive control presents challenges due to its reliance on an implicit, non-minimal input-output data-driven representation. By considering the class of constrained LTI systems with unknown time delays, we propose a set-theoretic direct data-driven predictive controller that does not require a
Mohammad Bajelani +2 more
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Regularization for Covariance Parameterization of Direct Data-Driven LQR Control
IEEE Control Systems LettersSubmitted to C-LSS and ...
Feiran Zhao +2 more
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On Direct vs Indirect Data-Driven Predictive Control [PDF]
2021 60th IEEE Conference on Decision and Control (CDC), 2021 In this work, we compare the direct and indirect approaches to data-driven predictive control of stochastic linear time-invariant systems. The distinction between the two approaches lies in the fact that the indirect approach involves identifying a lower dimensional model from data which is then used in a certainty-equivalent control design, while the ...
Vishaal Krishnan, Fabio Pasqualetti
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Harnessing uncertainty for a separation principle in direct data-driven predictive control [PDF]
Automatica, 2023 17 pages, 2 figures, 1 table, accepted by Automatica on October 31st, 2024 (first submission: December 22nd, 2023)
Alessandro Chiuso +3 more
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Direct data-driven control approach of reference shaping for two degree of freedom control
SICE Journal of Control, Measurement, and System Integration, 2022 In this study, we propose a novel data-driven approach for control of two degrees of freedom systems. The proposed method uses one-shot experimental data to derive the reference governor for improving control performance.
Motoya Suzuki, Osamu Kaneko
doaj +1 more source
Data-Driven Gradient Descent Direct Adaptive Control for Discrete-Time Nonlinear SISO Systems [PDF]
Electronics, 2014 A novel data-driven gradient descent (GD) adaptive controller, for discrete-time single-input and single output (SISO) systems, is presented. The controller operates as the least mean squares (LMS) algorithm, applied to a nonlinear system with feedback ...
Igor R. Krcmar +2 more
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AutoDDC: Hyperparameter Tuning for Direct Data-Driven Control
IEEE Control Systems, 2023 In many control applications, model-based design has become the standard practice due to the obvious advantages of a convenient, understandable description of the process and the possibility of a continuous validation of the controlled system at all ...
V. Breschi, S. Formentin
semanticscholar +1 more source