公开(公告)号：US20200380196A1

公开(公告)日：2020-12-03

申请号：US16909825

申请日：2020-06-23

Applicant: HUNAN UNIVERSITY OF SCIENCE AND TECHNOLOGY

Inventor： Xiaoping ZHANG ,  Ji LIU ,  Ruirui ZHANG

IPC: G06F30/398

Abstract: Taking parameters of a main circuit in a BBMC as optimization objects, and a total harmonic distortion of an output voltage of the BBMC, a deviation between an actual output current and a corresponding rated output current as optimization objectives, a mathematical model between optimization objects and optimization objectives is established. A multi-objective optimization satisfaction function and a multi-objective optimization fitness function are established by selecting a current rating as a rated output current of the BBMC. An adaptive wolf pack optimization algorithm is adopted to obtain a set of optimal parameters of the main circuit. The rated output current is changed to obtain n sets of optimal parameters, and functional relationships between the optimal parameters of the main circuit in the BBMC are obtained using a numerical fitting method. Optimal parameters of the main circuit corresponding to different current ratings are determined according to the functional relationships.

公开(公告)号：US20200320234A1

公开(公告)日：2020-10-08

申请号：US16909753

申请日：2020-06-23

Applicant: HUNAN UNIVERSITY OF SCIENCE AND TECHNOLOGY

Inventor： Xiaoping ZHANG ,  Ji LIU

IPC: G06F30/20 ,  G05B13/04 ,  H02M3/158

Abstract: A mathematical model between the optimization objects and the optimization objectives is established, with finite-time control parameters as optimization objects, and a total harmonic distortion of an output voltage, a deviation signal of a capacitor voltage and a deviation signal of an output current of BBMC as optimization objectives. A multi-objective optimization satisfaction function and a multi-objective optimization fitness function are established. Multiple sets of optimal finite-time control parameters are iteratively optimized using an adaptive wolf pack algorithm. Functional relationships between respective optimal finite-time control parameters and the corresponding actual output current of BBMC are obtained using a numerical fitting method. Optimal control parameters corresponding to any load are obtained according to the obtained functional relationships. Therefore, the control parameters are adjusted in real time according to the functional relationships and the load of the BBMC-based speed regulation system or the actual output current of BBMC.