no code implementations • 3 Jul 2023 • Chongzhi Wang, Haibin Shao, Dewei Li
The positive/negative definite matrices are strong in the multi-agent protocol in dictating the agents' final states as opposed to the semidefinite matrices.
no code implementations • 22 Sep 2022 • Lulu Pan, Haibin Shao, Yang Lu, Mehran Mesbahi, Dewei Li, Yugeng Xi
We show that the vector-valued PPAC problem can be solved via associated matrix-weighted networks with the higher-dimensional agent state.
no code implementations • 28 Aug 2022 • Lulu Pan, Haibin Shao, Mehran Mesbahi, Dewei Li, Yugeng Xi
Inspired by the observation that the link redundancy in a network may degrade its diffusion performance, a distributed data-driven neighbor selection framework is proposed to adaptively adjust the network structure for improving the diffusion performance of exogenous influence over the network.
no code implementations • 7 May 2022 • Yaru Yu, Dewei Li, Dongya Zhao, Yugeng Xi
The major novelty of the proposed input-mapping sliding mode control strategy lies in that the sliding mode surface and the sliding mode controller are co-designed through online learning from historical input-output data to minimize an objective function.
no code implementations • 26 Jan 2022 • Zihao Sheng, Lin Liu, Shibei Xue, Dezong Zhao, Min Jiang, Dewei Li
Further, an evaluation is designed to make a decision on lane change, in which safety, efficiency and comfort are taken into consideration.
no code implementations • 26 Oct 2021 • Lulu Pan, Haibin Shao, Yuanlong Li, Dewei Li, Yugeng Xi
The Zeno phenomenon can be excluded for both cases under the proposed coordination strategy.
no code implementations • 27 Sep 2021 • Zihao Sheng, Yunwen Xu, Shibei Xue, Dewei Li
This paper proposes a graph-based spatial-temporal convolutional network (GSTCN) to predict future trajectory distributions of all neighbor vehicles using past trajectories.
no code implementations • 26 Jul 2021 • Haibin Shao, Lulu Pan, Mehran Mesbahi, Yugeng Xi, Dewei Li
For distributed implementation, a quantitative connection between entries of Laplacian eigenvectors and the "relative rate of change" in the state between neighboring agents is further established; this connection facilitates a distributed algorithm for each agent to identify "favorable" neighbors to interact with.
no code implementations • 20 Jul 2021 • Lulu Pan, Haibin Shao, Mehran Mesbahi, Dewei Li, Yugeng Xi
Second, if the underlying network switches amongst infinite number of networks, the matrix-weighted integral network is employed to provide sufficient conditions for cluster consensus and the quantitative characterization of the corresponding steady-state of the multi-agent system, using null space analysis of matrix-valued Laplacian related of integral network associated with the switching networks.
no code implementations • 11 Jun 2021 • Lulu Pan, Haibin Shao, Dewei Li, Lin Liu
This paper examines the event-triggered consensus of the multi-agent system on matrix-weighted networks, where the interdependencies among higher-dimensional states of neighboring agents are characterized by matrix-weighted edges in the network.
no code implementations • IEEE/CAA Journal of Automatica Sinica 2021 • Xiaoxing Ren, Dewei Li, Yugeng Xi, Haibin Shao
In this paper, we consider distributed convex optimization problems on multi-agent networks.
no code implementations • 28 Nov 2020 • Chongzhi Wang, Lulu Pan, Haibin Shao, Dewei Li, Yugeng Xi
We show that necessary and/or sufficient conditions for bipartite consensus on matrix-weighted networks can be characterized by the uniqueness of the non-trivial balancing set, while the contribution of the associated non-trivial intersection of null spaces to the steady-state of the matrix-weighted network is examined.
no code implementations • 21 Oct 2016 • Dewei Li, Yingjie Tian
To improve the performance, the idea of multi-view learning is implemented and three kinds of features are provided, each one corresponds to a single view.