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논문 기본 정보

자료유형
학술저널
저자정보
Jung-Chu Ting (National Changhua University of Education) Der-Fa Chen (National Changhua University of Education)
저널정보
전력전자학회 JOURNAL OF POWER ELECTRONICS JOURNAL OF POWER ELECTRONICS Vol.18 No.5
발행연도
2018.9
수록면
1,380 - 1,397 (18page)

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The synchronous reluctance motor (SynRM) servo-drive system has highly nonlinear uncertainties owing to a convex construction effect. It is difficult for the linear control method to achieve good performance for the SynRM drive system. The nonlinear backstepping control system using upper bound with switching function is proposed to inhibit uncertainty action for controlling the SynRM drive system. However, this method uses a large upper bound with a switching function, which results in a large chattering. In order to reduce this chattering, a nonlinear backstepping control system using an adaptive law is proposed to estimate the lumped uncertainty. Since this method uses an adaptive law, it cannot achiever satisfactory performance. Therefore, a nonlinear backstepping control system using a reformed recurrent Hermite polynomial neural network with an adaptive law and an error estimated law is proposed to estimate the lumped uncertainty and to compensate the estimated error in order to enhance the robustness of the SynRM drive system. Further, the reformed recurrent Hermite polynomial neural network with two learning rates is derived according to an increment type Lyapunov function to speed-up the parameter convergence. Finally, some experimental results and a comparative analysis are presented to verify that the proposed control system has better control performance for controlling SynRM drive systems.

목차

Abstract
I. INTRODUCTION
II. CONFIGURATION OF A SYNRM DRIVE SYSTEM
III. CONTROL SYSTEM DESIGN
IV. EXPERIMENTAL RESULTS
V. CONCLUSIONS
REFERENCES

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