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Decoupling control is a commonly employed technique for achieving high precision in multiple-input multiple-output (MIMO) motion control systems. A static decoupling matrix, which can be determined using geometric construction, is widely used due to its practicality and simplicity. However, inaccurate geometric parameters will lead to a coarse decoupling matrix, and result in interactions among the system axes and performance deterioration. To tackle this challenge, various attempts have been undertaken to calibrate the decoupling matrix. Data-driven on-line approaches have gained considerable attention for their ability to calibrate the decoupling matrix without interrupting the normal operation of the system. This paper presents a data-driven approach to calibrate the decoupling matrix for MIMO and linear time invariant (LTI) systems. Through some reasonable assumptions, a calibrated static decoupling matrix can be derived to improve the performance of the system. Moreover, considering the inevitable presence of measurement noise, the consistency of the proposed method has been analyzed. As a result, the instrument variable is introduced in the improved method to eliminate the impact of the measurement noise. Finally, the effectiveness and practicality of the proposed method are demonstrated through both numerical simulations and experiments carried out on an ultraprecision wafer stage.
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http://dx.doi.org/10.1016/j.isatra.2024.05.002 | DOI Listing |
IEEE Trans Neural Netw Learn Syst
September 2025
In this article, we first tackle a more realistic domain adaptation (DA) setting: source-free blending-target DA (SF-BTDA), where we cannot access to source-domain data while facing mixed multiple target domains without any domain labels in prior. Compared to existing DA scenarios, SF-BTDA generally faces the coexistence of different label shifts in different targets, along with noisy target pseudolabels generated from the source model. In this article, we propose a new method called evidential graph contrastive alignment (EGCA) to decouple the blending-target domain and alleviate the effect of noisy target pseudolabels.
View Article and Find Full Text PDFMicromachines (Basel)
July 2025
School of Mechanical Engineering, North University of China, Taiyuan 030051, China.
A method for configuration synthesis of a reconfigurable decoupled parallel mechanical leg is proposed. In addition, a configuration evaluation index is proposed to evaluate the synthesized configurations and select the optimal one. Kinematic analysis and performance optimization of the selected mechanism's configuration are carried out, and the motion mode of the robot's reconfigurable mechanical leg is selected according to the task requirements.
View Article and Find Full Text PDFSensors (Basel)
August 2025
Department of Computer Science and Technology, College of Computer and Information Engineering, Inner Mongolia Agricultural University, Hohhot 010011, China.
Time series clustering finds wide application but is often limited by data quality and the inherent limitations of existing methods. Compared to high-dimensional structured data like images, the low-dimensional features of time series contain less information, and endogenous noise can easily obscure important patterns. When dealing with massive time series data, existing clustering methods often focus on mining associations between sequences.
View Article and Find Full Text PDFJ Chem Inf Model
September 2025
Aix Marseille Univ, CNRS, ICR, Marseille 13013, France.
Periodic boundary condition (PBC)-adapted formulations of quantum mechanics/molecular mechanics (QM/MM) methods allow for the accurate computation of free energies, provided there is sufficient phase-space sampling. In this work, we develop a robust and efficient QM/MM approach based on electrostatic potential fitted (ESPF) charge operators. The method combines smooth particle-mesh Ewald summation to describe QM-MM electrostatic interactions and the Ewald pair potential to treat long-range QM-QM interactions.
View Article and Find Full Text PDFJ Phys Chem A
September 2025
Max-Planck-Institut für Kohlenforschung, Kaiser-Wilhelm-Platz 1, D-45470 Mülheim an der Ruhr, Germany.
We present an efficient two-level strategy to accelerate the solution of the CASSCF linear-response eigenvalue problem using a customized Davidson algorithm. By identifying a subset of important response-vector components─the so-called P space─we compute and diagonalize full Hessian and metric matrix elements while treating the remaining Q-space components with a diagonal approximation. This approach decouples the orbital and configuration responses, enabling independent preconditioning of each component.
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