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In this paper, the adaptive friction compensation schemes are developed to provide much enhanced position tracking performance against nonlinear dynamic friction. The adaptive friction parameter observer possessing a simple structure and to be easy to implementation into controller is first studied to estimate the friction parameters. The process of the uncertainty approximation using the RFNN technique...
Sliding mode controller using a recurrent fuzzy neural network (RFNN) is presented, in which RFNN is utilized to estimate the real-time lumped uncertainty for the position control of permanent magnet linear synchronous motor (PMLSM) drive system, so that the control effort can be reduced. Considering the convergence rate, global feed-forward RFNN is employed instead of global feedback RFNN. Furthermore,...
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