Adaptive Robust Motion Control of an Ironless Permanent Magnet Linear Synchronous Motor with Dead-zone Compensation

被引:0
|
作者
Sun, Peng [1 ,2 ]
机构
[1] Chinese Acad Sci, Hefei Inst Phys Sci, Inst Adv Mfg Technol, Beijing, Peoples R China
[2] Changzhou Inst Adv Mfg Technol, Changzhou, Jiangsu, Peoples R China
来源
2019 22ND INTERNATIONAL CONFERENCE ON ELECTRICAL MACHINES AND SYSTEMS (ICEMS 2019) | 2019年
基金
中国国家自然科学基金;
关键词
adaptive robust control; dead-zone compensation; nonparametric uncertainty; permanent magnet linear synchronous motor; trajectory tracking control; NONLINEAR-SYSTEMS; INDUCTION-MOTOR; DYNAMICS;
D O I
暂无
中图分类号
TM [电工技术]; TN [电子技术、通信技术];
学科分类号
0808 ; 0809 ;
摘要
The ironless permanent magnet linear synchronous motor (ILPMLSM) is widely used in precision applications because of its advantages, such as direct drive, zero cogging and attractive force, and high speed and acceleration potential. In most of the existing control schemes, the adaptive robust control algorithm has special advantages in dealing with parameter uncertainties and uncertain nonlinearities of the linear motor systems. However, the previously ignored nonparametric uncertainty (noise and disturbance) is widespread in industrial applications. Furthermore, even small uncertainties may produce parameter drift possibly leading to instability of the control system, when the reference signals are not persistently exciting. In this paper, a nonlinear dynamic model of an ILPMLSM system including both the traditional various uncertainties and the previously ignored nonparametric uncertainty is given, leading to a better understanding of the parameter drift and system instability caused by the noise and disturbance. Additionally, an adaptive robust control scheme with dead-zone compensation is proposed. The dead-zone technique is employed to improve the discontinuous projection adaptation law. The approach of dead-zone compensation adaptive robust control is applied to synthesize the system controller for both accurate parameter estimation and a guaranteed robust performance to various uncertainties. Comparative experiments show that the proposed approach can achieve fast and accurate trajectory tracking, robustness, and stability against uncertainties mentioned above.
引用
收藏
页码:1330 / 1334
页数:5
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