Online Inertia Identification Algorithm Of AC Servo System Based On AKO-RLS

With the advancement of industrial automation and the booming of science and technology,the AC servo system has gradually become an indispensable execution device in industrial production.Its performance directly determines the precision and efficiency of automated machining.During the operation of the servo system,the parameter changes may cause the controller malfunction.This malfunction and unknown disturbance may lead to the performance degradation or even affect the stability of the system.Therefore,it is of great significance to identify system parameters effectively and correct controller parameters in real time.Among the many parameters affecting the servo system,the inertia of the system limits the speed loop bandwidth of the servo system.Besides,it is the key parameter of the speed loop controller design.So the accurate identification of the system inertia is crucial for the system performance improvement.This paper presents an online inertia identification algorithm for AC servo system.First,the kinematics equations of the system are discretized,and the recursive formula of the system inertia is constructed by the recursive least square(RLS)method,this method can obtain the unbiased estimation of parameters in the system with white noise.Considering the strong coupling relationship between moment of inertia and load torque,the load torque observer is designed according to the principle of Kalman filter,and the observed load torque from the Kalman observer(KO)is fed into the recursive formula of moment of inertia,so that the algorithm can be identified effectively under loading conditions.Next,an adaptive law is designed for the covariance matrix in the Kalman observer,so that in the process of experiment,the debugging of covariance parameters can be avoided.The adaptive Kalman observer(AKO)was used to carry out load torque observation.At the same time,comparison simulative and experimental results were carried out.It shows that the inertia identification algorithm with adaptive law can obtain more accurate moment of inertia of the system.Then the influence of velocity quantization error on the identification result is analyzed.The constraint of inertia identification error affected by velocity measurement result is obtained.According to the constraint relationship,the algorithm execution criterion,which is based on the speed difference threshold,can be obtained.And the calculation period of the algorithm can be adjusted by this criterion,which permits the algorithm to be performed under low acceleration,and one more step extend the applicable scope of the proposed methods in this paper.Finally,the proposed on-line inertia identification algorithm based on variable period AKO-RLS is verified by systematic experiments.The inertia identification experiments are carried out on the towing platform,the screw platform and the swing arm platform respectively.It shows that the algorithm can accurately and effectively identify the system inertia of the ideal experimental platform,friction platform and the condition of load torque variation,respectively.