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In addition, for tracking objectives in short command times, sliding mode controller performs more appropriately.
Simulation studies have shown that the presented adaptive design of fuzzy sliding mode controller performs very well in the presence of an unknown disturbance.
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It was found that the sliding mode controller performed best overall and that the addition of wind feedforward control did not significantly improve its effectiveness.
This shows the superior performance of the proposed sliding mode controller.
In addition, a comparison of the proposed control schemes with a fuzzy PID controller is performed; the results show that the proposed SDC-based sliding mode controller gave better results.
The sliding mode controller (SMC) is used for reducing the influence of uncertainties and external disturbances, and it performs fast responses.
To evaluate the manipulator design, the dynamic control compensation is performed on the basis of the conventional PID controller and the adaptive fuzzy sliding mode controller.
Nonlinear and intelligent controllers such as an internal model controller, a sliding mode controller, and a neurofuzzy controller are adopted in [18, 19, 20] to improve PET performance.
Open image in new window Fig. 5 Sliding mode controller.
The design of sliding mode controller involves two steps.
The fuzzy sliding mode controller combines the advantages of both fuzzy controllers and sliding mode controllers.
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