This paper presents a parameters tuning method based on the genetic algorithm (GA) for an active disturbance rejection control (ADRC) of a three-axis inertially stabilized platform (ISP) with imaging sensors. To improve the stabilization accuracy and robustness of an aerial ISP under multi-source disturbances environment, an ADRC control scheme is first proposed. Then, to accurately identify and tune the parameters in the ADRC controller, a GA-based parameters tuning method is proposed. In this way, the performance of the ADRC is superior to the empirical method. To validate the proposed method, the simulations and experiments are carried out. The results show that the proposed ADRC with GA-based parameters tuning method has significant disturbance rejection ability which can improve the stabilization accuracy obviously. Compared with the ADRC with empirically tuning method, the stabilization error (RMS) under movable base is decreased up to 50.09%.
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http://dx.doi.org/10.1016/j.isatra.2018.08.001 | DOI Listing |
Front Artif Intell
January 2025
Department of Radiation Oncology, Universitätsklinikum Erlangen, Friedrich-Alexander-Universität Erlangen-Nürnberg, Erlangen, Germany.
Introduction: Generating physician letters is a time-consuming task in daily clinical practice.
Methods: This study investigates local fine-tuning of large language models (LLMs), specifically LLaMA models, for physician letter generation in a privacy-preserving manner within the field of radiation oncology.
Results: Our findings demonstrate that base LLaMA models, without fine-tuning, are inadequate for effectively generating physician letters.
Front Artif Intell
January 2025
Language Intelligence and Information Retrieval (LIIR) Lab, Department of Computer Science, KU Leuven, Leuven, Belgium.
The digitization of healthcare records has revolutionized medical research and patient care, with electronic health records (EHRs) containing a wealth of structured and unstructured data. Extracting valuable information from unstructured clinical text presents a significant challenge, necessitating automated tools for efficient data mining. Natural language processing (NLP) methods have been pivotal in this endeavor, aiming to extract crucial clinical concepts embedded within free-form text.
View Article and Find Full Text PDFMid-infrared dual-comb spectroscopy offers significant advantages by combining the high sensitivity of mid-infrared spectroscopy with the high spectral resolution and rapid acquisition of the dual-comb method. However, its effective resolution, constrained by the inherent comb line spacing, hinders its ability to resolve narrow absorption features, common in critical applications such as sub-Doppler spectroscopy, low-pressure gas analysis, and construction of the atmospheric profile. To address this challenge, we present a synchronous offset frequency tuning method for the mid-infrared dual-comb system to improve effective resolution far beyond comb line spacing.
View Article and Find Full Text PDFThe flat-top beams have significant potential for applications in micromachining and biomedicine, due to their unique intensity distribution. Therefore, spatiotemporal flat-top beams, which are all flat-top in both spatial and time domains, may significantly advance its development. Here, we demonstrate the generation of a spatiotemporal flat-top beam using an all-fiber mode-locked laser.
View Article and Find Full Text PDFMulti-channel multiplexing metasurfaces have attracted considerable interest with the growing demand for multifunctional integration and enhanced communication capabilities. Dynamic tuning of electromagnetic waves with multiple degrees of freedom is a key approach to improving information processing capabilities. Metasurfaces with chiral meta-atoms and Janus metasurfaces with asymmetric transmission properties introduce new degrees of freedom for multiplexing technologies.
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