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This study is concerned with the synchronised tracking control for multiple agents with high-order dynamics, whereas the desired trajectory is only available for a portion of the team members. Using the weighted average of the neighbours' states as the reference signal, adaptive neural network (NN) control is designed for each agent in both full-state and output feedback cases. It is proved that the adaptive NN control law guarantees that the tracking error of each agent converges to an adjustable neighbourhood of the origin for both cases although some of them do not access the desired trajectory directly. Two simulation examples are provided to demonstrate the performance of the proposed approaches.