7 Papers
23 Citations
Yi Dong is an academic researcher from Nanjing University of Science and Technology. The author has contributed to research in topics: Adaptive control & Rendezvous. The author has an hindex of 5, co-authored 7 publications.
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Papers
The leader-following rendezvous with connectivity preservation via a self-tuning adaptive distributed observer
TL;DR: This paper studies the leader-following rendezvous with connectivity preservation problem for multiple double integrator systems subject to external disturbances via a self-tuning adaptive distributed observer approach that removes the existing assumption that all the followers know the system matrix of the leader system.
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A self-tuning adaptive distributed observer approach to the cooperative output regulation problem for networked multi-agent systems
TL;DR: A self-tuning distributed observer for a multi-agent system is proposed, which is capable of providing the estimation of the leader's signal to various followers without assuming all the followers know the system matrix.
12
Rendezvous with connectivity preservation for multi-robot systems with an unknown leader
TL;DR: A distributed control strategy is proposed to maintain the connectivity of the communication network, to achieve the asymptotic tracking of all the followers to the output of the unknown leader system, as well as to reject unknown external disturbances.
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Cooperative output regulation for networked multi-agent systems based on the self-tuning adaptive distributed observer
TL;DR: An adaptive distributed control law is developed to solve the cooperative output regulation problem for linear heterogeneous multi-agent systems and makes the least use of the information of the network and the Information of the leader system.
7
Cooperative robust output regulation for second-order nonlinear multi-agent systems with an unknown exosystem
TL;DR: The adaptive control technique and the robust control technique are combined to solve the adaptive stabilization problem for a modified augmented system composed of the given multi-agent system and the distributed internal model by a distributed adaptive robust state feedback controller.
7