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Distributed Adaptive Tracking Control for Synchronization of Unknown Networked Lagrangian Systems

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2 Author(s)
Gang Chen ; College of Automation, Chongqing University, Chongqing, China ; Frank L. Lewis

This paper investigates the cooperative tracking control problem for a group of Lagrangian vehicle systems with directed communication graph topology. All the vehicles can have different dynamics. A design method for a distributed adaptive protocol is given which guarantees that all the networked systems synchronize to the motion of a target system. The dynamics of the networked systems, as well as the target system, are all assumed unknown. A neural network (NN) is used at each node to approximate the distributed dynamics. The resulting protocol consists of a simple decentralized proportional-plus-derivative term and a nonlinear term with distributed adaptive tuning laws at each node. The case with nonconstant NN approximation error is considered. There, a robust term is added to suppress the external disturbances and the approximation errors of the NNs. Simulation examples are included to demonstrate the effectiveness of the proposed algorithms.

Published in:

IEEE Transactions on Systems, Man, and Cybernetics, Part B (Cybernetics)  (Volume:41 ,  Issue: 3 )