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RISS 인기검색어
- 검색키워드
- 저자 : Mingyang Xie (검색결과 3 건)
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Mingyang Xie,Muhammad Majid Gulzar,Huma Tehreem,Muhammad Yaqoob Javed,Syed Tahir Hussain Rizvi 제어·로봇·시스템학회 2020 International Journal of Control, Automation, and Vol.18 No.6
Importance of PV based energy systems cannot be denied with quickly increase in renewable energy demand. Due to inherent uncertainties and non-linear behaviour of grid tied PV system, conventional control strategies are unable to provide satisfactory performance. Therefore, key purpose of this paper is to design non linear controller for the control of grid tied PV system. A novel control strategy is devised by utilizing Lyapunov base finite time non-linear reactive power and dc link voltage control. This strategy employes Lyapunov approach to ensure stability and guarantees robustness. With this control strategy, better and superior performance is observed in comparison to proportional integral controller. Furthermore, simulation results are provided to illustrate the effectiveness of proposed algorithm. Various disturbances of system such as change in solar insolation level, change in reference parameters, faults on buses are considered. With this control strategy, settling time and oscillations are found significantly less than PI controller.
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Characteristics and Causes of Extreme Rainfall Induced by Binary Tropical Cyclones over China
Mingyang Wang,Fumin Ren,Yanjun Xie,Guoping Li,Ming-Jen Yang,Tian Feng 한국기상학회 2021 Asia-Pacific Journal of Atmospheric Sciences Vol.57 No.2
Binary tropical cyclones (BTC) often bring disastrous rainfall to China. From the viewpoint of the extreme of the BTC maximum daily rainfall, the characteristics of BTC extreme rainfall (BTCER) during 1960–2018 are analyzed, using daily rainfall data; and some representative large-scale mean flows, in which the associated BTCs are embedded, are analyzed. Results show that the frequency of BTCER shows a decreasing trend [−0.49 (10 yr)−1] and is mainly distributed within the BTC heavy rainstorm interval (100 mm≤ BTCER <250 mm). BTCER occurs mostly from July to September with a peak in August. Three BTCER typical regions— Minbei, the Pearl River Delta (PRD), and Taiwan—are identified according to the clustering of stations with high BTCER frequency and large BTCER. A further analysis of the 850-hPa BTC composite horizontal wind and water vapor flux over the PRD region shows the existence of two water vapor transport channels, which transport water vapor to the western tropical cyclone. In the first of these channels, the transport takes place via the southwest monsoon, which accounts for 58% of the total moisture, and an easterly flow associated with eastern tropical cyclone accounts for the remaining 42%. Binary tropical cyclones (BTC) often bring disastrous rainfall to China. From the viewpoint of the extreme of the BTC maximum daily rainfall, the characteristics of BTC extreme rainfall (BTCER) during 1960–2018 are analyzed, using daily rainfall data; and some representative large-scale mean flows, in which the associated BTCs are embedded, are analyzed. Results show that the frequency of BTCER shows a decreasing trend [−0.49 (10 yr) −1 ] and is mainly distributed within the BTC heavy rainstorm interval (100 mm ≤ BTCER <250 mm). BTCER occurs mostly from July to September with a peak in August. Three BTCER typical regions— Minbei, the Pearl River Delta (PRD), and Taiwan—are identified according to the clustering of stations with high BTCER frequency and large BTCER. A further analysis of the 850-hPa BTC composite horizontal wind and water vapor flux over the PRD region shows the existence of two water vapor transport channels, which transport water vapor to the western tropical cyclone. In the first of these channels, the transport takes place via the southwest monsoon, which accounts for 58% of the total moisture, and an easterly flow associated with eastern tropical cyclone accounts for the remaining 42%.
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Meta-Cognitive Fuzzy Neural Network Control for Active Power Filter
Ming Yang,Jienan Han,Qianwen Xie 제어로봇시스템학회 2021 제어로봇시스템학회 국제학술대회 논문집 Vol.2021 No.10
In this paper, an adaptive robust meta-cognitive fuzzy-neural-network control using sliding mode control is proposed for active power filter (APF), whereby a meta-cognitive fuzzy-neural-network (MCFNN) is employed to approximate modeling uncertainties. To overcome the drawbacks of conventional sliding mode control, the control law is constructed based on MCFNN rather than the actual systems. Unlike the predefined structure approaches, MCFNN is able to adapt the structure and parameters of the networks using the input information. Moreover, only the parameters of the rule nearest to the current input are adjusted online to reduce redundant or inefficient computation. Subsequently the Lyapunov stability analysis is presented to guarantee tracking performance and stability of the closed-loop system. Simulation studies demonstrate that the proposed control methods exhibit excellent performance in both steady state and transient operation.
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