NDLI: Distributed adaptive three-dimension formation control based on improved RBF neural network for non-linear multi-agent time-delay systems

Content Provider	IET Digital Library
Author	Zhang, Mingyang Yu, Xinyi Ding, Peixuan Ou, Linlin Zhang, Weidong
Abstract	Based on the improved radial basis function (RBF) neural networks, the distributed three-dimension formation control scheme in the presence of dynamic uncertainties is studied for non-linear multi-agent systems with time delay. A virtual leader which tracks the desired signal is followed by all agents adaptively. Linear reduced-order observers are designed on the basis of absolute and local state errors of each agent. The local state error and absolute state error are generated between neighbouring agents and each individual agent in formation, respectively. The time delay for each agent in the formation can be offset by designing a Lyapunov function, which can simplify the controller design. To deal with non-linear dynamic uncertainties and unavoidable disturbance, improved RBF neural networks are employed. In comparison with traditional RBF neural networks, improved RBF neural networks can provide better convergence performance. Subsequently, the formation controller is designed and the stability of the systems is validated by using a new Lyapunov function. Numerical simulation is conducted to demonstrate the effectiveness of the proposed method for non-linear multi-agent time-delay systems.
Starting Page	2758
Ending Page	2765
Page Count	8
ISSN	17518644
Volume Number	13
e-ISSN	17518652
Issue Number	Issue 17, Nov (2019)
Alternate Webpage(s)	https://digital-library.theiet.org/content/journals/iet-cta/13/17
Alternate Webpage(s)	https://digital-library.theiet.org/content/journals/10.1049/iet-cta.2018.6130
Journal	IET Control Theory & Applications
Publisher Date	2019-06-11
Access Restriction	Open
Rights Holder	© The Institution of Engineering and Technology
Subject Keyword	Absolute State Error Adaptive Control Control System Analysis Control System Synthesis Controller Design Delay System Distributed Adaptive Three-dimension Formation Control Distributed Parameter Control System Linear Reduced-order Observers Linear System Lyapunov Function Lyapunov Method Modelling And Identification Multi-agent System Multi-robot System Multivariable Control System Neural Nets Neurocontrol Neurocontrollers Nonlinear Control System Nonlinear Dynamic Uncertainties Nonlinear Multiagent Time-delay System Observers Radial Basis Function Network Radial Basis Function Neural Network RBF Neural Network Reduced Order System Self Adjusting Control System Simulation Stability Stability in Control Theory Synthesis Method 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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