Observer gain adaptation of output feedback sliding mode controller with support vector machine regression

Abstract

The conventional sliding mode controller needs the exact knowledge of system state measurements. In this study, nonlinear second order systems with unmeasured system states and bounded external disturbances are considered. The sliding mode observer based on nonlinear observation error dynamics is considered and the observer gain is adjusted by using a support vector machine based plant model. From the output of the support vector machine model, k-step ahead predictions are obtained. Therefore, the value of k is first analyzed to search for a proper value. It is also shown with the simulations that the stability conditions are satisfied for the chosen observer gains. Computer simulations are presented to show the effect of the proposed gain adjustment mechanism on the performance of output feedback sliding mode controller. It is seen that the trajectory tracking performance is improved with respect to a conventional output feedback sliding mode control scheme having constant sliding mode observer gains.