Observer-based output feedback containment control of a class of nonlinear multi-agent systems via adaptive neural control method
Tingru Xu, Jianting Lyu, Xin Yang, Xin Wang · 2020
This paper investigates containment control problem for a class of nonlinear multi-agent systems with multiple dynamic leaders, where the condition of zero control input for leader is not assumed. The dynamics of the each subsystem are assumed to be unknown and are estimated using neural networks. A local observer is used to estimate the states and an observer-based neural network controller is designed to guarantee that followers converge to the convex hull spanned by the leaders. Numerical simulations are finally given to show the effectiveness of the obtained results.