Sampled-data fuzzy control for a class of nonlinear systems with missing data and disturbances

Abstract

This paper considers the sampled-data fuzzy control of nonlinear systems in strict feedback form with disturbances and random missing input data. We propose a novel method in which a state observer and a disturbance observer are combined to construct a sampled-data fuzzy output feedback controller. The stochastic variables with a Bernoulli distributed sequence are used to model missing input data. Fuzzy logic systems are applied to approximate nonlinearities without requiring prior knowledge. The relation between observer gain and sampling period is established. The output feedback controller designed guarantees that the nonlinear system is globally stable. A simulation example of four degrees of freedom robotic arm is used to demonstrate the effectiveness and applicability of the proposed control scheme.