Abstract

This paper investigates robust stability analysis and stabilization of delay and uncertain systems approximated by a Takagi-Sugeno (T-S) fuzzy model. An innovative approach is proposed to develop delay-dependent stability criteria of the systems, which makes use of less-redundant information to construct Lyapunov function, employs an integral equation method to handle the cross-product terms, and alleviates the requirements of the bounding technique and model transformations that have been popularly adopted in many existing references. This leads to significant improvement in the stability performance with far fewer unknown variables in the stability computation. From the derived stability criteria, a new memoryless state-feedback control is further developed. The controller gain and the maximum allowable delay bound of the closed-loop control system can be obtained simultaneously by solving an optimization problem. Numerical examples are also given to demonstrate the theoretical results.

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