基于变周期递推最小二乘法与卡尔曼观测器的伺服系统在线惯量辨识

doi:10.19595/j.cnki.1000-6753.tces.L80178

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Abstract During the operation of AC servo system, the variation of system parameters and external disturbance will affect the performance of the system. The parameters of the system controller need to be adjusted in real time according to the system inertia. Therefore, it is of great importance to obtain the system inertia to achieve high performance servo system. In this paper, a variable period least square algorithm is proposed for on-line inertia identification, and the load torque is obtained by using Kalman observer. On the analysis of the quantization error of speed impact on the identification error, the speed difference is set as the criterion of identification algorithm implementation. The proposed method can obtain the inertia under low acceleration condition, and expand the scope of the identification algorithm. Simulation and experiment show that the proposed algorithm is effective.

Key words： Servo system variable period recursive least square Kalman observer inertia

Received: 28 June 2018 Published: 15 February 2019

PACS:

TM351

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	Articles by authors
	Yang Ming
	Qu Wanying
	Chen Yangyang
	Xu Dianguo

Cite this article:

Yang Ming,Qu Wanying,Chen Yangyang等. On-Line Inertia Identification of Servo System Based on Variable Period Recursive Least Square and Kalman Observer[J]. Transactions of China Electrotechnical Society, 2018, 33(zk2): 367-376.

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https://dgjsxb.ces-transaction.com/EN/10.19595/j.cnki.1000-6753.tces.L80178 OR https://dgjsxb.ces-transaction.com/EN/Y2018/V33/Izk2/367

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