LAUSR

This paper focuses on the fast finite-time tracking consensus for uncertain nonlinear multi-agent systems. By gracefully combining the hierarchical decomposition, adding a barrier power integrator and disturbance compensation techniques, a new adaptive fast finite-time controller is proposed. Compared with the existing works, the proposed method has several distinguishing features: 1) It can achieve fast finite-time convergence with full state constraints; 2) It can deal with some fully unknown nonlinearities and state-dependent disturbances. Moreover, the nonlinearities can be related with the states of all the followers; 3) The input of the leader is not required to be zero, meaning a broad class of references signals can be generated; 4) The controller is computationally simply and ready to be implemented. No fuzzy logic/neural networks are needed. Applications of the proposed method on multiple servo motors are also studied, which verifies the advantages over the existing methods.