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In this paper we deal with one of the most challenging control problems - controlling a class of underactuated systems with uncertainties. A synthesized integral sliding mode controller (ISMC) is proposed. The ISMC, constructed with a suitably chosen integral sliding surface, is able to completely nullify the influence from any matched factors, especially the matched uncertainties. As a consequence,...
This paper presents the method of discrete-time sliding mode control (DT-SMC) for a class of nonlinear time-delay systems via Takagi-Sugeno (T-S) fuzzy model. First, the discrete-time linear model with uncertainties and tine-varying delay is derived by employing T-S model to represent original system. Then the control problem becomes the robust stabilization controller design for linear uncertain...
A new second order sliding modes type-2 fuzzy controller for nonlinear uncertain perturbed systems is developed in this paper. To overcome the constraint on the knowledge of the system model, local models related to some operating points were used to synthesize a type-2 nominal fuzzy global model. For sliding modes, two adaptive fuzzy type-2 systems have been introduced to generate the two super twisting...
In this paper, two kinds of controllers are proposed, which are adaptive fuzzy sliding mode control and advanced adaptive fuzzy sliding mode control. These approaches use an adaptive fuzzy system to approximate the system whose model has uncertainty. The sliding mode control part is used to guarantee the stability of the system and resistant the disturbance in the control channel. Further more, advanced...
A sliding mode controller with the adaptive parameters is proposed for a class of uncertain nonlinear systems such that the sliding mode parameter lambda , the approximate sign function parameter mu , the tendency rate k0 and the gain parameter eta be scheduled by the system states. Meanwhile, the obtained systems have the desired stable sliding mode motions with the appropriate parameters lambda...
A B-spline neural-network-based variable structure controller (VSC) for a class of nonlinear systems with parameter uncertainties is presented. The neural networks compensator is used to compensate the uncertainties in the systems. The tracking performance and stability is guaranteed by the VSC controller. The asymptotical stability of overall systems is verified by the Lyapunov stability criterion...
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