Adaptive Fuzzy Finite-Time Command Filtered Control for Stochastic Nonlinear Systems With Unmodeled Dynamics and Dead-Zone Constraints

In this article, the issue of adaptive fuzzy finite-time command filtered control is discussed for nonlinear stochastic systems subject to unknown dead-zone constraints and unmodeled dynamics. The packaged unknown nonlinearities are approximated by introducing fuzzy logic systems. An improved technique is introduced to cope with unknown functions with the structure of nonstrict-feedback in the operation of controller design. Under the criterion of finite-time stability, a novel fast convergent control scheme is developed. Additionally, the effect of filter errors bought by the command filters is diminished via applying corresponding error compensating signals and a measurable dynamic signal is adopted to handle unmodeled dynamics. The improved designed controller not only guarantees all the closed-loop signals remain finite-time bounded, but also makes the system output follows the given desirable trajectory under the bounded error. The usefulness of the designed strategy can be verified through the numerical and practical examples.