DRO

作品数：199被引量：319H指数：9
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Distributed stochastic model predictive control for energy dispatch with distributionally robust optimization
《Applied Mathematics and Mechanics(English Edition)》2025年第2期323-340,共18页Mengting LIN Bin LI C.C.ECATI 
Supported by the National Natural Science Foundation of China(No.U24B20156);the National Defense Basic Scientific Research Program of China(No.JCKY2021204B051);the National Laboratory of Space Intelligent Control of China(Nos.HTKJ2023KL502005 and HTKJ2024KL502007)。
A chance-constrained energy dispatch model based on the distributed stochastic model predictive control(DSMPC)approach for an islanded multi-microgrid system is proposed.An ambiguity set considering the inherent uncer...
关键词：distributed stochastic model predictive control(DSMPC) distributionally robust optimization(DRO) islanded multi-microgrid energy dispatch strategy 
Distributionally robust model predictive control for constrained robotic manipulators based on neural network modeling
《Applied Mathematics and Mechanics(English Edition)》2024年第12期2183-2202,共20页Yiheng YANG Kai ZHANG Zhihua CHEN Bin LI 
Project supported by the National Natural Science Foundation of China(Nos.62273245 and 62173033);the Sichuan Science and Technology Program of China(No.2024NSFSC1486);the Opening Project of Robotic Satellite Key Laboratory of Sichuan Province of China。
A distributionally robust model predictive control(DRMPC)scheme is proposed based on neural network(NN)modeling to achieve the trajectory tracking control of robot manipulators with state and control torque constraint...
关键词：robotic manipulator trajectory tracking control neural network(NN) distributionally robust optimization(DRO) model predictive control(MPC) 
Effects of nozzle and fluid properties on the drop formation dynamics in a drop-on-demand inkjet printing被引量：1
《Applied Mathematics and Mechanics(English Edition)》2019年第9期1239-1254,共16页A. B. AQEEL M. MOHASAN Pengyu LV Yantao YANG Huiling DUAN 
Project supported by the National Natural Science Foundation of China(No.11802004)
The droplet formation dynamics of a Newtonian liquid in a drop-on-demand (DOD) inkjet process is numerically investigated by using a volume-of-fluid (VOF) method. We focus on the nozzle geometry, wettability of the in...
关键词：INKJET printing drop-on-demand (DOD) droplet formation NOZZLE geometry surface wettability PRINTABILITY range 
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