Title
Consensus Maneuvering for a Class of Nonlinear Multivehicle Systems in Strict-Feedback Form.
Abstract
In this paper, a consensus maneuvering problem for nonlinear multivehicle systems in strict-feedback form is investigated. The consensus maneuvering problem includes a geometric task and a dynamic task. The geometric task means that all trajectories of follower vehicles converge to a parameterized path. The dynamic task is to drive the system to satisfy a desired dynamic assignment. A consensus maneuvering controller is developed for each vehicle based on a modular design approach. First, an estimator module is designed based on an echo state network, which is used to estimate uncertain nonlinearities. Then, a controller module is designed based on a modified dynamic surface control method through the use of a second-order nonlinear tracking differentiator. Finally, a path update law is designed based on a distributed maneuvering error feedback and a filtering scheme. The proposed controller is distributed in the sense that the path information is accessed by a small number of follower vehicles only. The stability of the closed-loop system cascaded by the estimator module and the controller module is analyzed based on input-to-state stability theory and cascade theory. Simulation results are provided to demonstrate the efficacy of the proposed consensus maneuvering controllers for uncertain nonlinear strict-feedback systems.
Year
DOI
Venue
2019
10.1109/TCYB.2018.2822258
IEEE transactions on cybernetics
Keywords
Field
DocType
Task analysis,Vehicle dynamics,Stability analysis,Nonlinear dynamical systems,Reservoirs,Closed loop systems,Cybernetics
Control theory,Mathematical optimization,Nonlinear system,Differentiator,Control theory,Vehicle dynamics,Echo state network,Mathematics,Estimator,Stability theory,Strict-feedback form
Journal
Volume
Issue
ISSN
49
5
2168-2275
Citations 
PageRank 
References 
1
0.35
0
Authors
3
Name
Order
Citations
PageRank
Yibo Zhang181.77
Dan Wang271438.64
Zhouhua Peng364536.02