Results 151 to 160 of about 1,084,598 (183)
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From learning to safety: A Direct Data-Driven Framework for Constrained Control
arXiv.orgEnsuring safety in the sense of constraint satisfaction for learning-based control is a critical challenge, especially in the model-free case. While safety filters address this challenge in the model-based setting by modifying unsafe control inputs, they
Kanghui He +3 more
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Robust direct data‐driven controller tuning with an application to vehicle stability control
International Journal of Robust and Nonlinear Control, 2017SummaryIn direct data‐driven controller tuning, a mathematical model of the plant is not needed, as the control law is directly derived from experimental data. Because the most widely used data‐driven techniques are based on the assumption that the underlying dynamics – albeit unknow – is linear, the performance of the resulting controller may not be ...
FORMENTIN, SIMONE +3 more
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Secure Data Reconstruction: A Direct Data-Driven Approach
IEEE Transactions on Automatic ControlThis article addresses the problem of secure data reconstruction for unknown systems, where data collected from the system are susceptible to malicious manipulation. We aim to recover the real trajectory without prior knowledge of the system model.
Jiaqi Yan, Ivan Markovsky, J. Lygeros
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One Equation to Rule Them All - Part I: Direct Data-Driven Cascade Stabilisation
arXiv.orgIn this article we present a framework for direct data-driven control for general problems involving interconnections of dynamical systems. We first develop a method to determine the solution of a Sylvester equation from data.
Junyu Mao +3 more
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Bias correction and instrumental variables for direct data-driven model-reference control
arXiv.orgManaging noisy data is a central challenge in direct data-driven control design. We propose an approach for synthesizing model-reference controllers for linear time-invariant (LTI) systems using noisy state-input data, employing novel noise mitigation ...
Manas Mejari +3 more
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A System Parameterization for Direct Data-Driven Estimator Synthesis
IEEE Control Systems LettersThis letter introduces a novel parameterization to characterize unknown linear time-invariant systems using noisy data. The presented parameterization describes exactly the set of all systems consistent with the available data.
Felix Brändle, Frank Allgöwer
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Noise Sensitivity of the Semidefinite Programs for Direct Data-Driven LQR
IEEE Transactions on Automatic ControlIn this article, we study the noise sensitivity of the semidefinite program (SDP) proposed for direct data-driven infinite-horizon linear quadratic regulator (LQR) problem for discrete-time linear time-invariant systems.
Xiong Zeng, Laurent Bako, Necmiye Ozay
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Data-Driven Direct Adaptive Risk-Sensitive Control of Stochastic Systems
Journal of Systems Science and ComplexityzbMATH Open Web Interface contents unavailable due to conflicting licenses.
Nan Qiao 0012, Tao Li 0002
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Kernel-Based Error Bounds of Bilinear Koopman Surrogate Models for Nonlinear Data-Driven Control
IEEE Control Systems LettersWe derive novel deterministic bounds on the approximation error of data-based bilinear surrogate models for unknown nonlinear systems. The surrogate models are constructed using kernel-based extended dynamic mode decomposition to approximate the Koopman ...
Robin Strässer +4 more
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