This paper proposes distributed optimal attitude consensus control for single-integrator multi rigid bodies with undirected network evolving on Special Orthogonal Group SO(3) while simultaneously guarantees the connectivity preservation property for agents using descent gradient algorithm. Since by Use of the Euclidean distance on Lie group as a measure of the energy of the state does not define and preserve the topology of SO(3); besides, solving the Hamilton-Jacobi-Bellman equation in optimal control problems shows difficulty implementing Euclidean distances and limits the results for SO(3) configuration state spaces. As a result, in this paper, the generic distance on SO(3) associated to the natural Riemannian metric structure is used. Using this structure, Firstly, a distributed potential function based consensus control law is applied to the system exploiting Riemannian distance on SO(3). Then, for relaxing some restrictive conditions, finite-time convergence, and increasing the speed of convergence the kinematic optimal control on SO(3) is considered. Referring to the proposed potential function designed in the previous section, an inverse optimal attitude consensus control problem is considered, which is solved by an inverse optimal control method. Finally, the designed method validates via two simulation examples.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
customersupport@researchsolutions.com
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
This site is protected by reCAPTCHA and the Google Privacy Policy and Terms of Service apply.
Copyright © 2025 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.