J
Jingyan Song
Researcher at Tsinghua University
Publications - 88
Citations - 1080
Jingyan Song is an academic researcher from Tsinghua University. The author has contributed to research in topics: Control theory & Attitude control. The author has an hindex of 16, co-authored 88 publications receiving 975 citations. Previous affiliations of Jingyan Song include The Chinese University of Hong Kong.
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Proceedings ArticleDOI
Short-term traffic flow forecasting based on Markov chain model
TL;DR: Gaussian Mixture Model (GMM), whose parameters are estimated with Expectation Maximum (EM) algorithm, is applied to approximate the transition probability and the representation of the optimal forecasting is given in terms of the parameters in GMM.
Journal ArticleDOI
Adaptive Sliding Mode Fault-Tolerant Control of the Uncertain Stewart Platform Based on Offline Multibody Dynamics
TL;DR: In this article, the authors proposed an adaptive sliding mode fault-tolerant control scheme based on offline multibody dynamics for the uncertain Stewart platform under loss of actuator effectiveness.
Journal ArticleDOI
Complex recurrent neural network for computing the inverse and pseudo-inverse of the complex matrix
Jingyan Song,Yeung Yam +1 more
TL;DR: A complex recurrent neural network is formulated and applied to compute the complex matrix inverse in real time to extend recent works which apply real recurrent networks for real-valued matrix inversion.
Journal ArticleDOI
A new hybrid navigation algorithm for mobile robots in environments with incomplete knowledge
TL;DR: The simulation results show that compared with three traditional algorithms based on different architectures, the new hybrid navigation algorithm proposed in this paper performs more reliable in terms of escaping from traps, resolving conflicts between layers and decreasing the computational time for avoiding time out of the control cycle.
Journal ArticleDOI
Real‐time motion planning for mobile robots by means of artificial potential field method in unknown environment
Tao Zhang,Yi Zhu,Jingyan Song +2 more
TL;DR: An improved wall‐following approach for real‐time application in mobile robots that greatly weakens the blindness of decision making of robot and it is very helpful to select appropriate behaviors facing to the changeable situation.