MAO Dinghui, QIU Jianqi, SHI Cenwei

 

(College of Electrical Engineering, Zhejiang University, Hangzhou 310027, China)

 

 

Abstract: Aiming at improving the control performance of induction motors and weakening the influence of load inertia variation, experimental study on inertia identification and parameter selftuning was carried out based on dSPACE device. Based on the mathematical model of motor, the expression between output and inertia of the system can be transformed to the standard form of leastsquare method. An improved leastsquare algorithm was applied to identify the inertia. With some proper assumptions and simplifications, the PI controller factors of the speed loop can be decided by the linear relationship with the moment of inertia. The hardware in loop simulation was established based on Matlab/Simulink and dSPACE device and experiments of load torque variation and inertia variation was carried out. The results indicate that the selftuning system can tune the control parameters automatically based on the identified inertia, expand parameter selection range, accelerate dynamic performance, restrain fluctuations and improve control performance for variable load.

 

Key words: induction motor; parameter selftuning; inertia; PI factors