In this paper, the main objective is to identify the parameters of motors, which includes a brushless direct current (BLDC) motor and an induction motor. The motor systems are dynamically formulated by the mechanical ...In this paper, the main objective is to identify the parameters of motors, which includes a brushless direct current (BLDC) motor and an induction motor. The motor systems are dynamically formulated by the mechanical and electrical equations. The real-coded genetic algorithm (RGA) is adopted to identify all parameters of motors, and the standard genetic algorithm (SRGA) and various adaptive genetic algorithm (ARGAs) are compared in the rotational angular speeds and fitness values, which are the inverse of square differences of angular speeds. From numerical simulations and experimental results, it is found that the SRGA and ARGA are feasible, the ARGA can effectively solve the problems with slow convergent speed and premature phenomenon, and is more accurate in identifying system’s parameters than the SRGA. From the comparisons of the ARGAs in identifying parameters of motors, the best ARGA method is obtained and could be applied to any other mechatronic systems.展开更多
This paper presents a novel dual-mode step-up （boost） DC/DC converter. Pulse-frequency modulation （PFM） is used to improve the efficiency at light load. This converter can operate between pulse-width modulation （...This paper presents a novel dual-mode step-up （boost） DC/DC converter. Pulse-frequency modulation （PFM） is used to improve the efficiency at light load. This converter can operate between pulse-width modulation （PWM） and pulse-frequency modulation. The converter will operate in PFM mode at light load and in PWM mode at heavy load. The maximum conversion efficiency of this converter is 96%. The conversion efficiency is greatly improved when load current is below 100 mA. Additionally, a soft-start circuit and a variable-sawtooth frequency circuit are proposed in this paper. The former is used to avoid the large switching current at the start up of the converter and the latter is utilized to reduce the EMI of the converter.展开更多
文摘In this paper, the main objective is to identify the parameters of motors, which includes a brushless direct current (BLDC) motor and an induction motor. The motor systems are dynamically formulated by the mechanical and electrical equations. The real-coded genetic algorithm (RGA) is adopted to identify all parameters of motors, and the standard genetic algorithm (SRGA) and various adaptive genetic algorithm (ARGAs) are compared in the rotational angular speeds and fitness values, which are the inverse of square differences of angular speeds. From numerical simulations and experimental results, it is found that the SRGA and ARGA are feasible, the ARGA can effectively solve the problems with slow convergent speed and premature phenomenon, and is more accurate in identifying system’s parameters than the SRGA. From the comparisons of the ARGAs in identifying parameters of motors, the best ARGA method is obtained and could be applied to any other mechatronic systems.
基金the National Science Council of Taiwan, China, under Grant No. NSC 95-2221-E-305010.
文摘This paper presents a novel dual-mode step-up （boost） DC/DC converter. Pulse-frequency modulation （PFM） is used to improve the efficiency at light load. This converter can operate between pulse-width modulation （PWM） and pulse-frequency modulation. The converter will operate in PFM mode at light load and in PWM mode at heavy load. The maximum conversion efficiency of this converter is 96%. The conversion efficiency is greatly improved when load current is below 100 mA. Additionally, a soft-start circuit and a variable-sawtooth frequency circuit are proposed in this paper. The former is used to avoid the large switching current at the start up of the converter and the latter is utilized to reduce the EMI of the converter.
