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pro vyhledávání: '"STEGAGNO, PAOLO"'
This paper presents a two-layer control framework for Autonomous Underwater Vehicles (AUVs) designed to handle uncertain nonlinear dynamics, including the mass matrix, previously assumed known. Unlike prior studies, this approach makes the controller
Externí odkaz:
http://arxiv.org/abs/2409.02745
Autor:
Jandaghi, Emadodin, Stein, Dalton L., Hoburg, Adam, Stegagno, Paolo, Zhou, Mingxi, Yuan, Chengzhi
This paper addresses the problem of composite synchronization and learning control in a network of multi-agent robotic manipulator systems with heterogeneous nonlinear uncertainties under a leader-follower framework. A novel two-layer distributed ada
Externí odkaz:
http://arxiv.org/abs/2403.00987
A high-gain observer-based cooperative deterministic learning (CDL) control algorithm is proposed in this chapter for a group of identical unicycle-type unmanned ground vehicles (UGVs) to track over desired reference trajectories. For the vehicle sta
Externí odkaz:
http://arxiv.org/abs/2002.10059
Publikováno v:
In IFAC PapersOnLine 2022 55(37):548-553
Publikováno v:
In IFAC PapersOnLine 2022 55(37):333-338
Publikováno v:
In IFAC PapersOnLine 2022 55(37):13-18
Publikováno v:
In Neurocomputing 21 May 2020 390:168-184
Publikováno v:
Autonomous Robots February 2016, Volume 40, Issue 2, pp 245-265, First online: 11 July 2015
We present a control framework for achieving encirclement of a target moving in 3D using a multi-robot system. Three variations of a basic control strategy are proposed for different versions of the encirclement problem, and their effectiveness is fo
Externí odkaz:
http://arxiv.org/abs/1307.7170
Publikováno v:
In Neurocomputing 6 November 2019 365:239-248
Publikováno v:
In Journal of the Franklin Institute July 2019 356(10):5049-5072