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A novel high performance torque control scheme for switched reluctance motors(SRMs) is proposed based on online fuzzy neural network modeling and adaptive sliding-mode current control. Firstly, an adaptive neural fuzzy inference system(ANFIS) is designed to learn the nonlinear static position-torque-current characteristic and the flux-linkage characteristic of an SRM offline. Then each phase torque...
In this paper, an indirect adaptive control scheme based on Takagi-Sugeno (TS)-type recurrent fuzzy models is proposed for nonlinear plants with unmeasurable states. The TS-type recurrent fuzzy model is used as the dynamic model of the nonlinear plant. Its recurrent property comes from that it can memorize temporal information with the feedback connections between its states layer and inputs layer,...
This paper presents a Takagi-Sugeno (T-S) fuzzy model based indirect adaptive control algorithm for a class of uncertain multiple-input-multiple-output (MIMO) nonlinear systems. The T-S model consisting of a set of affine fuzzy local models is used to model a nonlinear uncertain system. Local integral controllers are designed based on local affine fuzzy models corresponding to different operating...
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