This investigation proposes a dynamic event-triggered-based anti-disturbance control technique for the uncertain linear parameter varying (LPV) systems subject to multiple disturbances. The disturbances are comprised of two parts including the unavailable modeled disturbances and the available unmodeled disturbances. First, an observer is constructed to capture the unavailable modeled disturbances. Then, a dynamic event-triggered-based feedback controller is proposed. Further, under the developed event-triggered controller, sufficient conditions are presented for the uncertain LPV systems to achieve the multiple disturbances suppression and communication transmission resources saving. In the end, the reasonability of the raised dynamic event-triggered based anti-disturbance control scheme is verified by an example of a turbofan.

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.