Abstract
A new enhanced adaptive fuzzy sliding mode control approach is proposed in this article with its good availability for application in control of a highly uncertain nonlinear two-link pneumatic artificial muscle manipulator. Stability demonstration of the robust convergence of the closed-loop pneumatic artificial muscle manipulator system based on a novel enhanced adaptive fuzzy sliding mode control is experimentally proved using Lyapunov stability theorem. Obtained result confirms that the new enhanced adaptive fuzzy sliding mode control method, applied to the two-link uncertain nonlinear pneumatic artificial muscle manipulator system, is fully investigated with better robustness and precision than the standard sliding mode control and fuzzy sliding mode control techniques.
Highlights
Up to now, it is evident to recognize the benefits of sliding mode control (SMC) related to maintain robust to uncertainties and external noises
Verify both fuzzy SMC (FSMC) algorithms[22,23] and the new advanced enhanced adaptive fuzzy sliding mode control (EAFSMC) algorithm related to two principal concepts: the flexibility of the fuzzy set in use and the results that EAFSMC adaptively and robustly ensures during the control of a highly nonlinear serial pneumatic artificial muscle (PAM) robot
The novel EAFSMC approach is able to adaptively estimate online the dynamic features of the 2-DOF serial PAM robot presented in equation (41)
Summary
It is evident to recognize the benefits of sliding mode control (SMC) related to maintain robust to uncertainties and external noises. Based on the abovementioned results this article introduces a novel enhanced adaptive fuzzy sliding mode control (EAFSMC) approach which will be tested on the highly nonlinear serial PAM robot. Verify both FSMC algorithms[22,23] and the new advanced EAFSMC algorithm related to two principal concepts: the flexibility of the fuzzy set in use and the results that EAFSMC adaptively and robustly ensures during the control of a highly nonlinear serial PAM robot It comparatively tests the availability of online tuning approach, the number of fuzzy if- laws installed of the new EAFSMC controller, the tracking precision performance, and the total time-consuming computation criteria, respectively.
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