NDLI: Distributed finite-time tracking control for multiple uncertain Euler–Lagrange systems with input saturations and error constraints

Content Provider	IET Digital Library
Author	Chen, Liangliang Li, Chuanjiang Sun, Yanchao Ma, Guangfu
Abstract	This study addresses the distributed finite-time tracking control for multiple uncertain Euler–Lagrange systems with input saturations and error constraints. In order to achieve distributed finite-time tracking control in the model-independent way, neural networks are used to approximate the system unknown terms. Besides, the authors consider that there exists input saturation for each dimension of each follower in the systems. The input saturations are tackled by converting the systems with input saturations to the cases with unknown input gains. Then, based on backstepping technique, the distributed finite-time tracking control law is developed. Tan-type barrier Lyapunov function is utilised to guarantee that the error variables would not exceed the predefined bounds. Lyapunov theory and graph theory demonstrate the finite-time stability of the systems. By choosing a class of two-link manipulators consisting of one leader and four followers, numerical simulations are provided to show the effectiveness of the proposed control algorithm.
Starting Page	123
Ending Page	133
Page Count	11
ISSN	17518644
Volume Number	13
e-ISSN	17518652
Issue Number	Issue 1, Jan (2019)
Alternate Webpage(s)	https://digital-library.theiet.org/content/journals/iet-cta/13/1
Alternate Webpage(s)	https://digital-library.theiet.org/content/journals/10.1049/iet-cta.2018.5802
Journal	IET Control Theory & Applications
Publisher Date	2018-11-20
Access Restriction	Open
Rights Holder	© The Institution of Engineering and Technology
Subject Keyword	Closed Loop System Combinatorial Mathematics Distributed Control Distributed Finite-time Tracking Control Error Constraint Finite-time Stability Graph Theory Input Saturation Lyapunov Method Manipulators Multiple Uncertain Euler–Lagrange Systems Multivariable Control System Neural Network Neurocontrol Neurocontrollers Stability Stability in Control Theory Tan-type Barrier Lyapunov Function Tracking Two-link Manipulators Uncertain System
Content Type	Text
Resource Type	Article
Subject	Control and Optimization Control and Systems Engineering Human-Computer Interaction Electrical and Electronic Engineering Computer Science Applications

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