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Copyright of Light Industry Machinery is the property of Light Industry Machinery Editorial Office and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Control Theory & Applications / Kongzhi Lilun Yu Yinyong is the property of Editorial Department of Control Theory & Applications and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Journal of Image & Graphics is the property of Editorial Office of Journal of Image & Graphics and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Research & Exploration in Laboratory is the property of Research & Exploration in Laboratory and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Aiming at the problems of low efficiency,torque ripple and noise problem of brushless DC motor driven by traditional control method,the reasons for these phenomena were analyzed,a novel kind of sinusoidal wave drive strategy based on the vector control was proposed for BLDC and the brushless DC motor control system was developed.Inverter driving circuit,protection circuits for overvoltage as well as overcurrent and other hardware circuit were designed at the core of STM32F103VE controller.The results indicate that compared to sixstep commutation method,vector control can decrese the fluctuation of the commutation current by 52％,alleviate torque ripple and reduce running noise,which is quite suitable for equipments sensitive to running noise,such as air conditioner,kitchen ventilator.Thus,it has high application value. [ABSTRACT FROM AUTHOR]

A fuzzy adaptive algorithm is proposed for the imperfections of tracking a maneuvering target using conventional algorithm based on current statistical model. Maneuvering frequency is adjusted in real time by fuzzy reasoning according to the normalized residual and its change rate. Acceleration variance is depicted using residual power function, and the mean value of current acceleration is updated by the de- viation between the estimated and predicted values of acceleration. On this basis, the weight of proposed algorithm is revised by Gauss membership function and strong tracking algorithm. Fuzzy adaptive algorithm is not restricted by maneuvering frequency given manually and extreme value of maximum acceleration, which is suitable for the different ranges and degrees of maneuvering. The performance of the proposed algorithm is tested by tracking three typical maneuvering targets, such as step maneuvering, circular maneuvering, and Jerk maneuvering. Simulated results show the tracking range is expanded using the pro- posed algorithm compared with the conventional tracking algorithm based on current model and the adaptive algorithm based on Jerk model. The proposed algorithm has good steady-state and transient characteristics, and its tracking accuracy and convergence rate are superior to those of the other two algorithms. [ABSTRACT FROM AUTHOR]