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An Hinfin robust controller based on local feedback recurrent neural network (RNN) is proposed for the position tracking control of the permanent magnet linear synchronous motor (PMLSM). The proposed local feedback RNN with a simple-architecture is employed to estimate dynamic mapping of lumped element uncertainty. Based on the result of RNN, the quadric form function of the Hinfin robust controller...
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,...
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,...
An Hinfin robust controller based on local feedback recurrent neural network (RNN) is proposed for the position tracking control of the permanent magnet linear synchronous motor (PMLSM). The proposed local feedback RNN with a simple-architecture is employed to estimate dynamic mapping of lumped element uncertainty. Based on the result of RNN, the quadric form function of the Hinfin robust controller...
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