Adaptive Fuzzy Backstepping Asymptotic Disturbance Rejection of Multiagent Systems With Unknown Model Dynamics

This article presentsan adaptive fuzzy asymptotic disturbance rejection scheme for multiagent mechanical systems with unknown model dynamics and unknown frequency disturbances. The mechanical motion equations are expressed as the parameterized equations and the disturbances are described by unknown parametric exogenous system. The unknown parametric exogenous system is transformed into the canonical model with unknown disturbances as the inputs. The disturbance filter provides estimations of the state vector in the canonical model such that disturbances are represented as parameterized forms with exponentially decaying errors. The disturbance rejection can be converted into the adaptive control. Based on the adaptive vectorial fuzzy backstepping, the disturbance rejection formation controller is designed with the fuzzy logic systems approximating the model unknown dynamics. The adaptive robust control term attenuates fuzzy approximation errors. In contrast to the existing results, the adaptive fuzzy disturbance rejection formation control realizes the estimation and rejection for unknown frequency disturbances without requiring the a priori knowledge of model dynamics. Based on the Barbalat’s lemma, it is shown that the adaptive disturbance rejection controller achieves the asymptotic formation tracking. Application on the surface vessel formation confirms the availability.