The concept of Arga and Bilig serves as a foundational principle in both ancient Mongolian philosophy and traditional Mongolian medicine (TMM). Arga, symbolized by brightness and associated with qualities of fire and ...The concept of Arga and Bilig serves as a foundational principle in both ancient Mongolian philosophy and traditional Mongolian medicine (TMM). Arga, symbolized by brightness and associated with qualities of fire and activity, complements Bilig, symbolized by darkness and representing attributes of water and stillness. Together, these opposing forces permeate all aspects of existence, from the genesis of parenthood to the interplay of day and night. Understanding Arga-Bilig is crucial for diagnosing and treating diseases, as it illuminates the source of imbalance within the body. This review provides an overview of the significance of Arga-Bilig in Mongolian philosophy and its application in TMM, emphasizing the dynamic interplay of these opposing forces and their role in maintaining balance and harmony within the body.展开更多
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
基金Science and Technology Young Talents Development Project of Inner Mongolia Autonomous Region(NJYT22048)Inner Mongolia Natural Science Foundation(2023LHMS08002)NMPA Key Laboratory Open Fund Project(MDK2023025).
文摘The concept of Arga and Bilig serves as a foundational principle in both ancient Mongolian philosophy and traditional Mongolian medicine (TMM). Arga, symbolized by brightness and associated with qualities of fire and activity, complements Bilig, symbolized by darkness and representing attributes of water and stillness. Together, these opposing forces permeate all aspects of existence, from the genesis of parenthood to the interplay of day and night. Understanding Arga-Bilig is crucial for diagnosing and treating diseases, as it illuminates the source of imbalance within the body. This review provides an overview of the significance of Arga-Bilig in Mongolian philosophy and its application in TMM, emphasizing the dynamic interplay of these opposing forces and their role in maintaining balance and harmony within the body.
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.
