In this paper, an adaptive anti-disturbance switching (AADS) control strategy is proposed for switched Takagi-Sugeno fuzzy systems (ST-SFSs) subject to multi-source disturbances. The disturbances consist of two parts: the available unmodeled disturbance and the disturbance modeled by dynamic neural network. Firstly, a novel adaptive disturbance observer is designed to approximate the dynamic neural network modeled disturbance. Secondly, the attenuation performance from the output to the available disturbance is analyzed by the L 2 gain index. Thirdly, a controller based on the adaptive disturbance observer is constructed for the ST-SFS under the average dwell time switching signal limitation. Further, under the designed adaptive disturbance observer, and the controller, a sufficient condition is established for the ST-SFS to realize multi-source disturbance suppression (DS). Finally, a mass-spring-damping simulation example is given to verify the rationality of the established AADS control scheme.