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Fault Diagnosis and Fault Tolerant Control for Manipulator with Actuator Multiplicative Fault
Yawei Wu,Lina Yao 제어·로봇·시스템학회 2021 International Journal of Control, Automation, and Vol.19 No.2
In this paper, a new fault diagnosis and fault tolerant control algorithm for manipulators with actuator multiplicative fault is proposed. The dynamic model of the manipulator with disturbance is taken as the research object. When faults occur in the actuator, a nonlinear observer based on radial basis function (RBF) neural network is used to estimate the fault information. After the fault information is obtained, an adaptive back-stepping sliding mode controller is used to control the manipulator to reach the desired trajectory. At last, an illustrated example is given to demonstrate the efficiency of the proposed algorithm, and satisfactory results have been obtained.
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Yawei Wu,Yifan Cui,Ronggang Ni,Shuxin Nie,Xinzhen Wu 전력전자학회 2019 ICPE(ISPE)논문집 Vol.2019 No.5
The performance of the initial rotor position detection of Permanent Magnet Synchronous Machines (PMSMs) at standstill depends much on the position observer. In this paper, the Extended State Observer (ESO) is compared with the traditional Proportional Integration (PI) observer adopting the rotating high frequency voltage injection algorithm, and the observer parameter design method is derived based on the bandwidth analysis of the close-loop transfer function. Experiments are carried out on a 3 kW PMSM prototype for verifications.
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Qiong Chen,Weiwei Wu,Hailan Yang,Ping Zhang,Yongliang Feng,Keke Wang,Ying Wang,Suping Wang,Yawei Zhang 대한당뇨병학회 2020 Diabetes and Metabolism Journal Vol.44 No.6
Background Identification of modifiable dietary factors, which are involved in the development of gestational diabetes mellitus (GDM), could inform strategies to prevent GDM. Methods We examined the dietary patterns in a Chinese population and evaluated their relationship with GDM risk using a case-control study including 1,464 cases and 8,092 control subjects. Propensity score matching was used to reduce the imbalance of covariates between cases and controls. Dietary patterns were identified using factor analysis while their associations with GDM risk were evaluated using logistic regression models. Results A “vegetable” dietary pattern was characterized as the consumption of green leafy vegetables (Chinese little greens and bean seedling), other vegetables (cabbages, carrots, tomatoes, eggplants, potatoes, mushrooms, peppers, bamboo shoots, agarics, and garlic), and bean products (soybean milk, tofu, kidney beans, and cowpea). For every quartile increase in the vegetables factor score during 1 year prior to conception, the first trimester, and the second trimester of pregnancy, the GDM risk lowered by 6% (odds ratio [OR], 0.94; 95% confidence interval [CI], 0.89 to 0.99), 7% (OR, 0.94; 95% CI, 0.88 to 0.99), and 9% (OR, 0.91; 95% CI, 0.86 to 0.96). Conclusion In conclusion, our study suggests that the vegetable dietary pattern is associated with lower GDM risk; however, the interpretation of the result should with caution due to the limitations in our study, and additional studies are necessary to explore the underlying mechanism of this relationship.
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