Sampled-data input-to-output stabilization of nonlinear system with dynamic uncertainties
Xi Chen, Lijun Zhu, Li Chai, Jing–Wen Yi · 2017
Input-to-output stabilization (IOS) problem with a specified gain arises from the synchronization of the networked systems in [1]. The approach for solving this problem is to establish a recursive procedure to calculate the gain from the external input to the state and the output. However, in sampled-data scenario, the aforementioned problem becomes more challenging particularly for systems with dynamic uncertainties, since the input-to-output property will be affected by the sampling phenomenon and especially sampling on dynamic uncertainties. In order to calculate the IOS gain for a sampled-data system, we have to develop a more complicated recursive procedure for which both the disturbance and the so-called sampling error term are viewed as the external input. Finally, the sampling period must be selected carefully to guarantee the IOS property for sampled-data control.