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논문 기본 정보

자료유형
학술저널
저자정보
Chih-Hong Lin (National United University)
저널정보
전력전자학회 JOURNAL OF POWER ELECTRONICS JOURNAL OF POWER ELECTRONICS Vol.16 No.4
발행연도
2016.7
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1,438 - 1,454 (17page)

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초록· 키워드

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Because the nonlinear and time-varying characteristics of continuously variable transmission (CVT) systems driven by means of a six-phase copper rotor induction motor (CRIM) are unconscious, the control performance obtained for classical linear controllers is disappointing, when compared to more complex, nonlinear control methods. A blend modified recurrent Gegenbauer orthogonal polynomial neural network (OPNN) control system which has the online learning capability to come back to a nonlinear time-varying system, was complied to overcome difficulty in the design of a linear controller for six-phase CRIM driving CVT systems with lumped nonlinear load disturbances. The blend modified recurrent Gegenbauer OPNN control system can carry out examiner control, modified recurrent Gegenbauer OPNN control, and reimbursed control. Additionally, the adaptation law of the online parameters in the modified recurrent Gegenbauer OPNN is established on the Lyapunov stability theorem. The use of an amended artificial bee colony (ABC) optimization technique brought about two optimal learning rates for the parameters, which helped reform convergence. Finally, a comparison of the experimental results of the present study with those of previous studies demonstrates the high control performance of the proposed control scheme.

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Abstract
I. INTRODUCTION
II. CONFIGURATION OF SIX-PHASE CRIM DRIVING CVT SYSTEM
III. BLEND MODIFIED RECURRENT GEGENBAUER OPNN CONTROL SYSTEM
IV. EXPERIMENTAL RESULTS
V. CONCLUSIONS
REFERENCES

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UCI(KEPA) : I410-ECN-0101-2017-560-000800062