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- 저자 : Xiangyong Hao (검색결과 3 건)
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Hebao Jia,Jing Wang,Hao Shen,Xiangyong Chen,Kaibo Shi 제어·로봇·시스템학회 2022 International Journal of Control, Automation, and Vol.20 No.6
This paper focuses on the H∞ synchronization issue for fuzzy neural networks via a dynamic eventtriggered sliding mode control scheme. In order to relieve the congestion phenomenon in the communication channel, a dynamic event-triggered mechanism is introduced into the sliding mode control design, in which an internal dynamical variable is adopted to fit the event-triggered condition suitably. Moreover, some results with less conservatism are obtained by considering the asynchronous premise variable problem. Then, sufficient criteria are established through the Lyapunov stability theory, which can guarantee that the sliding mode dynamics is asymptotically stable with a given H∞ performance. In this case, a dynamic event-triggered sliding mode control law is constructed to drive the trajectories of the fuzzy neural networks onto the designed sliding surface. Finally, the effectiveness and superiority of the presented method is verified by an illustrative example.
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An Improved Result on Stability Analysis of Delayed Load Frequency Control Power Systems
Shiyu Jiao,Jianwei Xia,Zhen Wang,Xiangyong Chen,Jing Wang,Hao Shen 제어·로봇·시스템학회 2021 International Journal of Control, Automation, and Vol.19 No.4
This paper investigates the stability of power systems with load frequency control considering time delays(constant and time-varying delays). A new criterion for ensuring the stability of the system is proposed on the basisof Lyapunov stability theory and a further strengthened inequality. Finally, taking a single-area load frequencycontrol scheme with the proportional-integral controller as an example, according to the stability criterion obtained,the relationship between the maximum allowable delay and the gain of proportional-integral controller is discussed. Besides, in case studies, the effectiveness of our method is also demonstrated.
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Liangliang Xu,Lian Li,Peng Wang,Ming Zhang,Yanfang Zhang,Xiangyong Hao,Lvnan Yan,Bo Li,Tianfu Wen,Mingqing Xu 거트앤리버 소화기연관학회협의회 2019 Gut and Liver Vol.13 No.6
Background/Aims: Microvascular invasion (MVI) is an established risk factor for hepatocellular carcinoma (HCC). However, prediction models that specifically focus on the individual prognoses of HCC patients with MVI is lacking. Methods: A total of 385 HCC patients with MVI were randomly assigned to training and validation cohorts in a 2:1 ratio. The outcomes were disease-free survival (DFS) and overall survival (OS). Prognostic nomograms were established based on the results of multivariate analyses. The concordance index (C-index), calibration plots and Kaplan-Meier curves were employed to evaluate the accuracy, calibration and discriminatory ability of the models. Results: The independent risk factors for both DFS and OS included age, tumor size, tumor number, the presence of gross vascular invasion, and the presence of Glisson’s capsule invasion. The platelet-tolymphocyte ratio was another risk factor for OS. On the basis of these predictors, two nomograms for DFS and OS were constructed. The C-index values of the nomograms for DFS and OS were 0.712 (95% confidence interval [CI], 0.679 to 0.745; p<0.001) and 0.698 (95% CI, 0.657 to 0.739; p<0.001), respectively, in the training cohort and 0.704 (95% CI, 0.650 to 0.708; p<0.001) and 0.673 (95% CI, 0.607 to 0.739; p<0.001), respectively, in the validation cohort. The calibration curves showed optimal agreement between the predicted and observed survival rates. The Kaplan-Meier curves suggested that these two nomograms had satisfactory discriminatory abilities. Conclusions: These novel predictive models have satisfactory accuracy and discriminatory abilities in predicting the prognosis of HCC patients with MVI after hepatectomy.
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