East China Jiaotong University

Nanchang Hangkong University

Crsc Research & Design Institute Group Co., Ltd.

Jiangxi Advanced Nanofiber S&t Co., Ltd

Qi Wang

Ling Liu

Junfeng Cui

Bin Liu

Yanli Zhou

Xiyou Liang

Duo Xu

Zijing Ding

Mengdi Miao

Libo Tan

Qinyang Song

Yuandong Xie

Yuxin Chen

Tiancheng Dong

Kunpeng Zhang

Changyuan Wang

Xiaoyi Lv

Chuyun Cheng

Haoqing Hou

Wen Ouyang

Yuming Wang

Disclosed is a wearable motion capture glove based on a flexible optical fiber, relating to the field of motion capture. The wearable motion capture glove includes a glove body, multiple motion acquisition sensing devices, and a glove packaging tool. Each motion acquisition sensing device includes a data acquisition and processing module, a circuit splint, and a flexible polymer profiled optical fiber. The data acquisition and processing module includes a motion capture data acquisition module, and a motion capture data processing module. The flexible optical fiber and the motion capture data acquisition module are firmly packaged using the circuit splint and the glove packaging tool, and then are fixed to a corresponding position of a finger joint of a wearer, such that the glove can be worn more closely to the finger joint, and data acquisition is more stable and accurate.

Wearable motion capture glove based on flexible optical fiber

A cooperative control method and system for electro-hydraulic hybrid braking of a middle-low speed maglev train is provided, which relates to the field of vehicle braking control. The method includes: denoising operation data of a middle-low speed maglev train; using a controlled autoregressive integrated moving average model as an electro-hydraulic hybrid braking process model for the middle-low speed maglev train, and processing denoised operation data by using a least square method to determine parameters in the controlled autoregressive integrated moving average model; establishing a generalized predictive control model with time lag compensation according to the controlled autoregressive integrated moving average model and a Smith predictor; and performing cooperative control on an electro-hydraulic hybrid braking process of the middle-low speed maglev train by using the generalized predictive control model with time lag compensation. A time lag in the electro-hydraulic hybrid braking process of the middle-low speed maglev train is reduced; control accuracy of the electro-hydraulic hybrid braking process of the middle-low speed maglev train is improved to a certain extent; and a speed tracking effect is improved.

Cooperative control method for electro-hydraulic hybrid braking of middle-low speed maglev train

Growing community of inventors

Nanchang, China

Qi Wang