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Cited by 62 publications
(32 citation statements)
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“…It is obvious that transfer function of LESO (16) contains an additional zeros compared to conventional LESO (15). From the frequency domain, it can provide sufficient amplitude attenuation and reduce phase lag.…”
Section: Analysis Of Conventional Leso and Lesomentioning
confidence: 99%
“…It is obvious that transfer function of LESO (16) contains an additional zeros compared to conventional LESO (15). From the frequency domain, it can provide sufficient amplitude attenuation and reduce phase lag.…”
Section: Analysis Of Conventional Leso and Lesomentioning
confidence: 99%
“…The structure of a traction network is very complicated because of a mass of multi-conductor transmission lines that are distributed, as well as the mutual coupling effect [5]. Therefore, considering the practical factors, such as the skin effect of lines and external disturbances, it is more reasonable to adopt a reduced-order method to model the traction network [5,32] than the Thevenin-equivalent method used in [33]. Avoiding a duplication of effort, the modeling process of the vehicle-grid coupling system is no longer described.…”
Section: System Verificationmentioning
confidence: 99%
“…Since 2008, the phenomenon has frequently occurred in China's high-speed railway depots. The LFO in railway is characterized by the amplitude fluctuation of grid-side voltage, current, and DC-side voltage, and happens when the multiple vehicles are concentrated in one power supply district and get power from a traction network [5]. With the larger voltage oscillation peak of the traction network, The paper is organized as follows.…”
Section: Introductionmentioning
confidence: 99%
“…The development of computer technology and advanced intelligent control theory provide a new way for the control of complex dynamic uncertain systems and the disturbance rejection. They have been gradually used in the control of ISP, such as neural network [10], genetic algorithm [11,12], fuzzy control [13,14], robust control [15], state compensation control [16], and autodisturbance rejection control [17]. Predictive control and fuzzy control are the effective methods to optimize the control of uncertain systems.…”
Section: Introductionmentioning
confidence: 99%