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The fuzzy sliding mode controller combines the advantages of both fuzzy controllers and sliding mode controllers.
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The sliding mode FNN controller combines the advantages of the sliding mode control with robust characteristics and the FNN with on-line learning ability.
The sliding mode fuzzy controller combines the advantages of both fuzzy controllers and sliding mode controllers.
An integral sliding mode controller is combined with the optimal controller to ensure robustness of the linear system which is affected by parametric uncertainties and external disturbances.
Second, a nonsingular terminal sliding mode controller (NTSMC) combined with neural network (NN) approximation is designed to track the commanded trajectory.
This work presents an adaptive fuzzy sliding mode controller (AFSMC) that combines a robust proportional integral control law for use in designing single-input single-output (SISO) nonlinear systems with uncertainties and external disturbances.
The aim of this work is the design of a sliding mode controller, which suitably combines simplex and super-twisting algorithms.
In order to improve the performance of single-input single-output (SISO) nonlinear systems with uncertainties, an adaptive fuzzy sliding mode controller (AFSMC) that combines linearization feedback is presented in this paper.
A hybrid controller combining sliding mode controller and adaptive fuzzy CMAC (AFCMAC) uncertainty compensator has been proposed for TDOFPPM.
The proposed FOSMC combines sliding mode controller (SMC) with fractional order dynamics, in which fractional order proportional-derivative (FOPD) sliding surface is adopted.
In this paper, a new nonlinear interconnected high-gain observer and a field-oriented control combined with a sliding mode controller for sensorless Induction Motors (IM) drive is proposed.
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