An H-infinity Output Tracking Control Approach to Sampled-Data Control for Nonlinear Networked Control Systems

In this article, we study the problem of H-infinity output tracking control and analyze the stability of nonlinear networked control systems with dynamic quantization, variable sampling intervals and communication delays. To improve the bandwidth utilization, an event-triggered mechanism is introduced in network control systems. Different from traditional periodic sampling control, the event trigger control adopted in this study is only controlled when the current sampling signal meets the triggering conditions, which can effectively reduce resource waste in network control systems by ensuring system control performance. By adopting input-delay and parallel distributed compensation (PDC) techniques, we establish an augment tracking model based on the Takagi-Sugeno (T-S) fuzzy model, in which the sampling interval of the sampler and the signal transmission delay are transformed into the refreshing interval of a zero-order holder (ZOH). Furthermore, we use the applicable lyapunov-krasovski-based approach to derive conditions expressed in linear matrix inequalities (LMIs), helping the problem to be accurately solved using the LMI toolbox in Matlab. Examples are given to illustrate the effectiveness of our results, especially the good tracking effect of the designed fuzzy controller.