An Adaptive Fuzzy Predictive Controller with Hysteresis Compensation for Piezoelectric Actuators

doi:10.1007/s12559-020-09722-8

	An Adaptive Fuzzy Predictive Controller with Hysteresis Compensation for Piezoelectric Actuators
	Wang, Ang1,2 ; Cheng, Long1,2 ; Yang, Chenguang 3; Hou, Zeng-Guang1,2
发表期刊	COGNITIVE COMPUTATION
ISSN	1866-9956
	2020-04-21
页码	12
通讯作者	Cheng, Long(long.cheng@ia.ac.cn)
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.
关键词	Adaptive fuzzy model Feedforward-feedback control Hysteresis compensation Model predictive control (MPC) Piezoelectric actuators (PEAs)
DOI	10.1007/s12559-020-09722-8
关键词[WOS]	DESIGN ; SYSTEMS
收录类别	SCI
语种	英语
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]
项目资助者	National Natural Science Foundation of China ; Beijing Natural Science Foundation
WOS研究方向	Computer Science ; Neurosciences & Neurology
WOS类目	Computer Science, Artificial Intelligence ; Neurosciences
WOS记录号	WOS:000528136000001
出版者	SPRINGER
七大方向——子方向分类	智能控制
引用统计	被引频次：9[WOS] [WOS记录] [WOS相关记录]
文献类型	期刊论文
条目标识符	http://ir.ia.ac.cn/handle/173211/39370
专题	复杂系统认知与决策实验室_先进机器人
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
第一作者单位	中国科学院自动化研究所
通讯作者单位	中国科学院自动化研究所
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.