Distributed Neural Network Control for Adaptive Synchronization of Uncertain Dynamical Multiagent Systems

This paper addresses the leader-follower synchronization problem of uncertain dynamical multiagent systems with nonlinear dynamics. Distributed adaptive synchronization controllers are proposed based on the state information of neighboring agents. The control design is developed for both undirected...

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Vydané v:IEEE transaction on neural networks and learning systems Ročník 25; číslo 8; s. 1508 - 1519
Hlavní autori: Peng, Zhouhua, Wang, Dan, Zhang, Hongwei, Sun, Gang
Médium: Journal Article
Jazyk:English
Vydavateľské údaje: New York, NY IEEE 01.08.2014
Institute of Electrical and Electronics Engineers
The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Predmet:
Algorithms
Applied sciences
Artificial neural networks
Computer science; control theory; systems
Computer Simulation
Computer systems and distributed systems. User interface
Control system synthesis
Control theory. Systems
Controllers
Design engineering
Distributed control
Dynamical systems
Exact sciences and technology
Feedback
Modelling and identification
Models, Theoretical
Multi-agent systems
Multiagent systems
neural network
Neural networks
Neural Networks (Computer)
Nonlinear dynamical systems
Nonlinear Dynamics
nonlinear multiagent system
Output feedback
Software
Stability analysis
Synchronism
Synchronization
Distributed control
synchronization
neural network
nonlinear multiagent system
Leadership
Non linear control
Control synthesis
Dynamical system
Adaptive control
Modeling
Adaptive method
Direct method
Uncertain system
Leader election
Observer
System identification
Stability
Bounded error
Transmission channel
Error bound
Neural network
Synchronization
Non linear system
Neurocontrollers
Multiagent system
Riccati equation
Output feedback
Directed graph
ISSN:2162-237X, 2162-2388, 2162-2388
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Popis
Shrnutí:This paper addresses the leader-follower synchronization problem of uncertain dynamical multiagent systems with nonlinear dynamics. Distributed adaptive synchronization controllers are proposed based on the state information of neighboring agents. The control design is developed for both undirected and directed communication topologies without requiring the accurate model of each agent. This result is further extended to the output feedback case where a neighborhood observer is proposed based on relative output information of neighboring agents. Then, distributed observer-based synchronization controllers are derived and a parameter-dependent Riccati inequality is employed to prove the stability. This design has a favorable decouple property between the observer and the controller designs for nonlinear multiagent systems. For both cases, the developed controllers guarantee that the state of each agent synchronizes to that of the leader with bounded residual errors. Two illustrative examples validate the efficacy of the proposed methods.
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ISSN:2162-237X
2162-2388
2162-2388
DOI:10.1109/TNNLS.2013.2293499