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An Adaptive Fuzzy Predictive Controller with Hysteresis Compensation for Piezoelectric Actuators

文献类型：期刊论文

作者Wang, Ang1,2; Cheng, Long1,2; Yang, Chenguang3; Hou, Zeng-Guang1,2
刊名COGNITIVE COMPUTATION
出版日期2020-04-21
页码12
关键词Adaptive fuzzy model Feedforward-feedback control Hysteresis compensation Model predictive control (MPC) Piezoelectric actuators (PEAs)
ISSN号1866-9956
DOI10.1007/s12559-020-09722-8
通讯作者Cheng, Long(long.cheng@ia.ac.cn)
英文摘要Piezoelectric actuators (PEAs) are the pivotal components of many nanopositioning systems because of their superiorities in bandwidth, mechanical force, and precision. Unfortunately, the intrinsic nonlinear property, hysteresis, makes it difficult to achieve the precise control of PEAs. Considering this drawback, diversified feedback control approaches have been studied in the literature. Inspired by the idea that the involvement of feedforward terms can upgrade the tracking performance, our previous conference paper proposed a novel feedforward-feedback control approach (model predictive control with hysteresis compensation). Following the previous work, an adaptive fuzzy predictive controller with hysteresis compensation is further studied in this paper. The major improvement of the proposed method is the employment of adaptive fuzzy model, by which the dynamic model of PEAs is able to adjust in real time, resulting in a better control performance. To validate the effectiveness of the proposed method, extensive experiments are conducted on a Physik Instrumente P-753.1CD piezoelectric nanopositioning stage. Comparisons with several existing control approaches are carried out, and the root mean square tracking error of the proposed method is reduced to 30% of that under the previously proposed neural network model-based predictive control, when tracking 100 Hz sinusoidal reference.
WOS关键词DESIGN ; SYSTEMS
资助项目National Natural Science Foundation of China[61873268] ; National Natural Science Foundation of China[U1913209] ; National Natural Science Foundation of China[61861136009] ; Beijing Natural Science Foundation[JQ19020]
WOS研究方向Computer Science ; Neurosciences & Neurology
语种英语
WOS记录号WOS:000528136000001
出版者SPRINGER
资助机构National Natural Science Foundation of China ; Beijing Natural Science Foundation
源URL[http://ir.ia.ac.cn/handle/173211/39369]  
专题自动化研究所_复杂系统管理与控制国家重点实验室_先进机器人控制团队
通讯作者Cheng, Long
作者单位1.Chinese Acad Sci, Inst Automat, State Key Lab Management & Control Complex Syst, Beijing 100190, Peoples R China
2.Univ Chinese Acad Sci, Sch Artificial Intelligence, Beijing 100049, Peoples R China
3.South China Univ Technol, Sch Automat Sci & Engn, Wushan Rd, Guangzhou 510640, Peoples R China
推荐引用方式
GB/T 7714		 Wang, Ang,Cheng, Long,Yang, Chenguang,et al. An Adaptive Fuzzy Predictive Controller with Hysteresis Compensation for Piezoelectric Actuators[J]. COGNITIVE COMPUTATION,2020:12.
APA Wang, Ang,Cheng, Long,Yang, Chenguang,&Hou, Zeng-Guang.(2020).An Adaptive Fuzzy Predictive Controller with Hysteresis Compensation for Piezoelectric Actuators.COGNITIVE COMPUTATION,12.
MLA Wang, Ang,et al."An Adaptive Fuzzy Predictive Controller with Hysteresis Compensation for Piezoelectric Actuators".COGNITIVE COMPUTATION (2020):12.

入库方式： OAI收割

来源：自动化研究所

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