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35 results on '"Cao, Jiawei"'

13. Short-Term Highway Traffic Flow Forecasting Based on XGBoost

Author

Ma Weifeng, Cao Jiawei, Yuefeng Cen, and Gang Cen

Subjects
Operations research, Computer science, 021105 building & construction, 0211 other engineering and technologies, 02 engineering and technology, 010502 geochemistry & geophysics, Traffic flow, 01 natural sciences, Intelligent transportation system, 0105 earth and related environmental sciences
Abstract

With the rapid development of urban intelligent transportation system, the prediction short-term of traffic flow attracts more and more attention. As the lack of the characteristics of traffic flow and appropriate models, the accurate predction of the traffic flow are facing a big challenge. A short-term traffic flow prediction model based on extreme gradient rise is proposed in this paper. The experiment results reveal the superiority of the modle by comparing with the traditional prediction model.

Published
2020

14. Synchronous Condenser Fault Diagnosis Method Based on RBF Neutral Network

Author

Ma Xiaoguang, Yu Guoqiang, Cao Jiawei, Xia Chao, and Liu Yanan

Subjects
Neutral network, Failure type, Artificial neural network, Control theory, Computer science, Calculation error, Synchronous condenser, Radial basis function, Diagnostic accuracy, Fault (power engineering)
Abstract

The traditional synchronous condenser fault diagnosis algorithm is too dependent on experience, and it cannot accurately reflect the relationship between features and failure type, resulting in the low diagnostic accuracy. Aiming at this problem, the radial basis function (RBF) neural network algorithm is used to diagnose the synchronous condenser fault. The operating parameters of synchronous condenser are used for learning and training, and the corresponding fault type output is obtained. The simulation results show that the diagnosis algorithm has a high accuracy and a small calculation error, proving that the diagnosis method can be widely used for on-line monitoring of the synchronous condenser.

Published
2019

15. Fault Early Warning, Fault Diagnosis and Intelligent Decision Platform Construction Technology for Condenser Based on Ubiquitous Internet of Things

Author

Zhiqiang Li, Gang Xu, Cao Jiawei, Dahai Yu, Guoqiang Yu, Lei Gao, and Chao Xia

Subjects
Warning system, Computer science, business.industry, Network security, Real-time computing, Cloud computing, AC power, Fault (power engineering), law.invention, law, Systems design, The Internet, business, Remote control
Abstract

Based on the detailed analysis and study of the advantages and disadvantages of the existing system, this paper develops a set of relatively perfect fault early warning, fault diagnosis and intelligent decision-making platform for the condenser based on the ubiquitous internet of things. The platform can realize the following functions. First is remote centralized monitoring of the operation state of the condenser. Second is intelligent early warning of the condenser. Third is remote fault diagnosis of the phase modulator. Forth is three-dimensional display and maintenance training of the condenser. The core technologies include data acquisition based on ubiquitous power internet of things, coordination governance among different databases and establishment of large data analysis platform, information mining technology based on large data analysis, cross-area data transmission and network security control technology, the remote on-line monitoring technology of the phase modulator. The system design mainly applies sensor technology, Internet technology, cloud computing technology, visualized intelligent diagnosis technology and reliability management technology to realize remote monitoring of the power network converter station’s phase modulator, including the monitoring of phase modulator operation parameters, reactive power remote control, remote monitoring of equipment operation status, coordinated operation status of the network and the machine. The results show that the platform of fault early warning, fault diagnosis and intelligent decision-making can apply sensor technology, Internet technology, cloud computing technology, visualized intelligent diagnosis technology and reliability management technology to realize remote monitoring of the phase modulator in power grid converter station, including the monitoring of the operation parameters of the phase modulator and the remote monitoring of reactive power, control and remote monitoring of equipment operation status, coordinated monitoring of machine network operation status, reliability management of electrical equipment, lubrication system and cooling system.

Published
2019

26. Control of a Soft Inchworm Robot With Environment Adaptation.

Author

Cao, Jiawei, Liang, Wenyu, Wang, Yuzhe, Lee, Heow Pueh, Zhu, Jian, and Ren, Qinyuan

Subjects
*SOFT robotics, *ROBOTS, *STRAIN energy, *APPROPRIATE technology, *ENERGY density, *REINFORCEMENT learning, *ROBOT kinematics
Abstract

Soft robots have recently evoked extensive attention because of their abilities to work effectively in unstructured environments. As an actuation technology of soft robots, dielectric elastomers (DEs) exhibit many intriguing attributes such as large strain and high energy density. This paper presents a novel, DE-based, soft crawling robot inspired by inchworms. The kinematics of the soft crawling robot is explored, and a data-driven model is developed to facilitate the controller design. The overall controller incorporates a feedforward controller, a feedback controller, and a disturbance observer (DOB). The feedback controller and the DOB will compensate the disturbance and model uncertainties resulting from the obtained dynamic model and ensure robust performance of the robot under different conditions. The effectiveness of the proposed control scheme is verified using experiments on surfaces made of different materials and with inclined angles. [ABSTRACT FROM AUTHOR]

Published
2020
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27. Control of Dielectric Elastomer Soft Actuators Using Antagonistic Pairs.

Author

Liang, Wenyu, Cao, Jiawei, Ren, Qinyuan, and Xu, Jian-Xin

Abstract

The inherent compliance and resilience allow soft robots to deal with unstructured environments. Among the various soft actuators explored for soft robotic applications, dielectric elastomer actuators (DEAs) stand out due to their intriguing advantages of large deformation, high energy density, fast response, and low cost. However, the viscoelasticity and the electromechanical coupling of these actuators increase the difficulty of the control design, especially for large deformation and/or high-speed operations. In this paper, the control issue of the DEAs is investigated. Inspired by the similarities between DEAs and biological muscles, an antagonistic actuation mechanism is proposed for DEAs control. Owing to the actions of the agonist can be compensated by the antagonist, the viscoelastic effects of the DEAs in antagonistic pairs can be compensated by each other. Moreover, a cerebellum-inspired adaptive learning controller for achieving accurate movements of the DEAs is designed and analyzed. To study the proposed actuation mechanism and controller, a simple 1-DOF manipulator based on two DEAs in an antagonistic pair is developed as a platform. Finally, several experiments have been conducted to test the developed system, and the results show that the proposed approach can achieve good performance even in large deformation and/or high-speed operations as well as strong robustness in disturbance rejection. [ABSTRACT FROM AUTHOR]

Published
2019
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33. Direct Torque Control of T-NPC Inverters-Fed Double-Stator-Winding PMSM Drives With SVM.

Author

Wang, Zheng, Wang, Xueqing, Cao, Jiawei, Cheng, Ming, and Hu, Yihua

Subjects
STATORS, ELECTRIC windings, TORQUE control, SUPPORT vector machines, VECTOR spaces, PERMANENT magnet motors
Abstract

This paper studies and proposes the vector space decomposition-based direct torque control (DTC) scheme for the T-type neutral-point-clamping (T-NPC) three-level inverters-fed double-stator-winding permanent magnet synchronous machine (PMSM) drive, which provides an effective solution for high-power high-reliability applications. The key is to propose a simple but effective space vector modulation (SVM) for DTC of T-NPC double-stator-winding drives-based two-step voltage vector synthesis, in such a way that good dynamic response and harmonic performance are obtained. The closed-loop controllers on harmonic subspace are incorporated to suppress the possible harmonics induced from back electromotive force and unbalanced parameters in phase windings of electrical machine. Furthermore, a hybrid current control is proposed for fault-tolerant operation of the T-NPC double-stator-winding PMSM drives under one-phase open-circuit conditions. In the hybrid current controller, the healthy winding still uses the SVM-DTC control while the faulty winding uses the closed-loop current controller to track the optimized current references. Both simulation and experimental results are presented to verify the performance of the proposed switching strategies and control schemes. [ABSTRACT FROM AUTHOR]

Published
2018
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