PROJECT TITLE :

New Results on Tracking Control Based on the T–S Fuzzy Model for Sampled-Data Networked Control System

ABSTRACT:

This study deals with the matter of $H_infty$ tracking control for a sampled-knowledge networked control system based on a Takagi–Sugeno fuzzy model. A mistake model is established by combining the input delay and parallel distributed compensation techniques therefore as to transform the sampling period of a sampler, an indication transmission delay, and knowledge packet dropouts to the refreshing interval of a zero-order hold. The tactic introduces a brand new augmented Lyapunov–Krasovskii purposeful to derive a sufficient condition to make sure a prescribed $H_infty$ tracking performance with less conservativeness than others. A fuzzy controller can simply be designed using the condition. A numerical example demonstrates the validity of the method.