NDLI: Cooperative adaptive finite-time control for stochastic multi-agent systems with input quantisation

Content Provider	IET Digital Library
Author	Zhang, Yan hui Sun, Jian He, Wei Li, Hong yi
Abstract	In this study, the finite-time cooperative tracking issue for non-linear multi-agent systems with stochastic disturbances is addressed. Different from the existing asymptotical stable control, the finite-time cooperative control can ensure the outputs of agents reach agree in finite time by raising a novel finite-time stability criterion. The radial basis function neural networks are employed to cope with the unknown non-linearities caused by the non-linear non-strict feedback form. Moreover, this study designs a new adaptive quantised control strategy to reduce communication burden. With such a control scheme, the tracking errors converge to a small area of the origin in finite time. Finally, some numerical simulation results are presented to testify the effectiveness of the approach proposed in this study.
Starting Page	746
Ending Page	754
Page Count	9
ISSN	17518644
Volume Number	13
e-ISSN	17518652
Issue Number	Issue 6, Apr (2019)
Alternate Webpage(s)	https://digital-library.theiet.org/content/journals/iet-cta/13/6
Alternate Webpage(s)	https://digital-library.theiet.org/content/journals/10.1049/iet-cta.2018.5330
Journal	IET Control Theory & Applications
Publisher Date	2019-01-23
Access Restriction	Open
Rights Holder	© The Institution of Engineering and Technology
Subject Keyword	Adaptive Control Adaptive Quantised Control Strategy Asymptotic Stability Closed Loop System Control Scheme Control System Analysis Control System Synthesis Existing Asymptotical Stable Control Feedback Finite Time Finite-time Control Input Quantisation Multi-agent System Neurocontrollers Nonlinear Control System Nonlinear Multiagent System Nonlinear Nonstrict Feedback Form Nonlinearities Novel Finite-time Stability Criterion Radial Basis Function Network Radial Basis Function Neural Network Self Adjusting Control System Stability Stability in Control Theory Stochastic Disturbances Stochastic Multiagent System Synthesis Method Time Varying Control System Time Varying System Tracking Issue
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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4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
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