Dissipative IT2 Fuzzy Control for Nonlinear Systems with Stochastic Occurring Sensor Saturation

This paper investigates the issue of dissipativity-based fuzzy control for nonlinear systems in the framework of interval type-2 (IT2) Takagi-Sugeno (T-S) fuzzy method. The uncertainties that exist in considered systems are depicted by lower and upper membership functions (LUMFs) and interrelated weighting functions. During designing a fuzzy controller, a crucial problem, stochastic occurring sensor saturation, which is built via the Bernoulli random distribution process, is taken into consideration. The controller design is more flexible since the membership functions (MFs) have diverse forms compared with studied systems. Based on Lyapunov stability theory, sufficient conditions are derived to guarantee the stochastic stability and strictly dissipative performance of closed-loop systems. Finally, simulation results are provided to illustrate the usefulness of the control approach proposed in this paper.