Research On Control System Of Asynchronous Motor Based On GA Optimization

Three-phase asynchronous motors are widely used in various fields because of their low cost,simple structure and good performance under harsh conditions.At the same time,with the improvement of production requirements,how to control the speed of asynchronous motor accurately and quickly has gradually become the focus of attention.In recent decades,the rapid development of power electronics technology has provided hardware basis for vector control variable frequency speed regulation technology of asynchronous motors.Moreover,intelligent control theory has been gradually applied to the design of asynchronous motor controller.Among them,fuzzy control is widely used because of its direct use of linguistic control rules,close to human logic,easy to understand,and no need for precise mathematical model of the controlled object in the design.Fuzzy-PID control,which combines fuzzy control with traditional PID control,can be used in the control system of asynchronous motor to further improve the dynamic and static performance of the motor.However,the performance of fuzzy PID control is closely related to the formulation of control rules.It depends on the experience of the designer.These characteristics result in the limitations of fuzzy PID control.Based on Darwin's evolutionary theory,genetic algorithm is simple and easy to implement.Combining with other algorithms,it can optimize the algorithm.Therefore,it is widely used in many engineering and scientific research fields.Firstly,the physical and mathematical models of asynchronous motor are analyzed,its complexity is pointed out,and the vector control principle of asynchronous motor is further introduced.Then,this paper introduces the principle and basic operation method of genetic algorithm,analyses and studies the premature problem of genetic algorithm in detail,puts forward a multi-population improvement strategy,and implements it by programming,which proves the feasibility of the improved genetic algorithm.Then,the improved genetic algorithm is used to optimize the control rules of the fuzzy controller.The fuzzy controller can automatically optimize the control rules without prior knowledge.Finally,the speed regulation performance of different regulators is simulated by different speed regulation requirements of asynchronous motor speed regulation system.Through the experimental results,the data of overshoot,anti-interference ability and speed error of different regulatorsystems are compared.The superiority of the improved genetic algorithm is proved.Figure [40] table [7] reference [46]...