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Neuro-adaptive Cooperative Tracking Control with Prescribed Performance of Unknown Higher-order Nonlinear Multi-agent Systems. (arXiv:1807.01165v1 [math.OC])
来源于:arXiv
This paper is concerned with the design of a distributed cooperative
synchronization controller for a class of higher-order nonlinear multi-agent
systems. The objective is to achieve synchronization and satisfy a predefined
time-based performance. Dynamics of the agents (also called the nodes) are
assumed to be unknown to the controller and are estimated using Neural
Networks. The proposed robust neuro-adaptive controller drives different states
of nodes systematically to synchronize with the state of the leader node within
the constraints of the prescribed performance. The nodes are connected through
a weighted directed graph with a time-invariant topology. Only few nodes have
access to the leader. Lyapunov-based stability proofs demonstrate that the
multi-agent system is uniformly ultimately bounded stable. Highly nonlinear
heterogeneous networked systems with uncertain parameters and external
disturbances were used to validate the robustness and performance of the new
novel approach 查看全文>>