Mutual Synchronization of Multiple Robot Manipulators with Unknown Dynamics
Journal of Intelligent and Robotic Systems
Modification and comparative analysis of smooth control laws for a group of agents
Automation and Remote Control
Distributed adaptive containment control of networked flexible-joint robots using neural networks
Expert Systems with Applications: An International Journal
Evolving intelligent system for the modelling of nonlinear systems with dead-zone input
Applied Soft Computing
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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.