Please use this identifier to cite or link to this item: https://hdl.handle.net/10356/146158
Title: Preview-based discrete-time dynamic formation control over directed networks via matrix-valued Laplacian
Authors: Cao, Kun
Li, Xiuxian
Xie, Lihua
Keywords: Engineering::Electrical and electronic engineering::Control and instrumentation::Control engineering
Engineering::Electrical and electronic engineering::Control and instrumentation::Robotics
Issue Date: 2020
Source: Cao, K., Li, X., & Xie, L. (2020). Preview-based discrete-time dynamic formation control over directed networks via matrix-valued Laplacian. IEEE Transactions on Cybernetics, 50(3), 1251-1263. doi:10.1109/TCYB.2019.2910534
Journal: IEEE Transactions on Cybernetics
Abstract: This paper studies the dynamic formation control problem for cooperative agents with discrete-time dynamics over directed graphs. Unlike using absolute coordinate, relative coordinate, interagent distance, or interagent bearing to specify the target formation and coordinate agents to achieve the formation, we study a coordination problem where the desired formation varies with time and only its geometric shape is predefined. Matrix-valued Laplacian approach has been adopted to address this problem in the continuous-time setting. However, the discrete-time counterpart is more challenging due to the constraint in information exchange. On the other hand, observe that in many real operations, at a given time instant, the agents will be able to plan their target formation configurations for a period of time ahead. We propose preview-based P-like and PD-like controllers for the formation control. The controllers with proper parameter setting are proved to be effective to address the dynamic formation control problem. Numerical simulations are given to validate the effectiveness of the proposed controllers.
URI: https://hdl.handle.net/10356/146158
ISSN: 2168-2267
DOI: 10.1109/TCYB.2019.2910534
Schools: School of Electrical and Electronic Engineering 
Research Centres: ST Engineering-NTU Corporate Lab 
Rights: © 2019 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works. The published version is available at: https://doi.org/10.1109/TCYB.2019.2910534
Fulltext Permission: open
Fulltext Availability: With Fulltext
Appears in Collections:EEE Journal Articles

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