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RISS 인기검색어
- 검색키워드
- 저자 : Jianfeng Xing (검색결과 3 건)
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Robust model predictive control for three-level voltage source inverters
Hong, Jianfeng,Zhang, Xing,Cao, Renxian The Korean Institute of Power Electronics 2021 JOURNAL OF POWER ELECTRONICS Vol.21 No.5
To solve the problem of parameter mismatch in model predictive control (MPC), this paper presents a robust model predictive control method based on a fixed window optimization (FWO) algorithm for a three-level voltage source inverter that only needs to sample the current value. When compared with the traditional observer-based model predictive control (such as the Luenberger observer, sliding mode observer (SMO) and Kalman filter (KMF)), the proposed method does not require an observer with a complicated design, and its algorithm is simple and easy to understand. Meanwhile, high current sampling accuracy is not needed in the proposed method. However, it is necessary in some types of model-free predictive control. In addition, low switching frequency operation and delay compensation are also considered in this paper. In general, the proposed method is simple to implement and does not have high requirements in terms of the accuracy of its current sensor. Experimental results show that the proposed method can accurately estimate parameter values and improve the parameter robustness of MPC.
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Zhanqiang Xing,Jianfeng Qu,Yi Chai,Qiu Tang,Yuming Zhou 대한기계학회 2017 JOURNAL OF MECHANICAL SCIENCE AND TECHNOLOGY Vol.31 No.2
The gear vibration signal is nonlinear and non-stationary, gear fault diagnosis under variable conditions has always been unsatisfactory. To solve this problem, an intelligent fault diagnosis method based on Intrinsic time-scale decomposition (ITD)-Singular value decomposition (SVD) and Support vector machine (SVM) is proposed in this paper. The ITD method is adopted to decompose the vibration signal of gearbox into several Proper rotation components (PRCs). Subsequently, the singular value decomposition is proposed to obtain the singular value vectors of the proper rotation components and improve the robustness of feature extraction under variable conditions. Finally, the Support vector machine is applied to classify the fault type of gear. According to the experimental results, the performance of ITD-SVD exceeds those of the time-frequency analysis methods with EMD and WPT combined with SVD for feature extraction, and the classifier of SVM outperforms those for K-nearest neighbors (K-NN) and Back propagation (BP). Moreover, the proposed approach can accurately diagnose and identify different fault types of gear under variable conditions.
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Ying Zhang,Hengyu Lei,Pengchong Wang,Qinyuan Zhou,Jie Yu,Xue Leng,Ruirui Ma,Danyang Wang,Kai Dong,Jianfeng Xing,Yalin Dong 한국생체재료학회 2023 생체재료학회지 Vol.27 No.00
Background Reactive oxygen species (ROS) overproduction and excessive hypoxia play pivotal roles in the initiation and progression of ulcerative colitis (UC). Synergistic ROS scavenging and generating O2 could be a promising strategy for UC treatment. Methods Ceria nanozymes (PEG-CNPs) are fabricated using a modified reverse micelle method. We investigate hypoxia attenuating and ROS scavenging of PEG-CNPs in intestinal epithelial cells and RAW 264.7 macrophages and their effects on pro-inflammatory macrophages activation. Subsequently, we investigate the biodistribution, pharmacokinetic properties and long-term toxicity of PEG-CNPs in mice. PEG-CNPs are administered intravenously to mice with 2,4,6-trinitrobenzenesulfonic acid-induced colitis to test their colonic tissue targeting and assess their anti-inflammatory activity and mucosal healing properties in UC. Results PEG-CNPs exhibit multi-enzymatic activity that can scavenge ROS and generate O2, promote intestinal epithelial cell healing and inhibit pro-inflammatory macrophage activation, and have good biocompatibility. After intravenous administration of PEG-CNPs to colitis mice, they can enrich at the site of colonic inflammation, and reduce hypoxia-induced factor-1α expression in intestinal epithelial cells by scavenging ROS to generate O2, thus further promoting disrupted intestinal mucosal barrier restoration. Meanwhile, PEG-CNPs can effectively scavenge ROS in impaired colon tissues and relieve colonic macrophage hypoxia to suppress the pro-inflammatory macrophages activation, thereby preventing UC occurrence and development. Conclusion This study has provided a paradigm to utilize metallic nanozymes, and suggests that further materials engineering investigations could yield a facile method based on the pathological characteristics of UC for clinically managing UC.
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