Adaptive Fuzzy Finite-Time Consensus Tracking for High-Order Stochastic Multi-agent Systems with Input Saturation

Xinyu Song, Lin Zhao

Abstract: This paper focuses on the finite-time tracking control for a class of stochastic nonlinear systems. A finite-time control law, combin ing command filter and adaptive backstepping is designed to achieve fast tracking and ensure the systems convergence to stability in finite time. Comparing with traditional backstepping, the advantage lies in the solving of the calculation explosion problem caused by the backstepping method when applied to the higher-order systems, at the same time the error compensation signal introduced in the process has a good perfor mance in eliminating the filter error. Moreover, the nonlinear functions mentioned in this paper are completely unknown, which are approxi mated by the adaptive neural network. Finally, a simulation is shown to prove the effectiveness of the designed controller.