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An Adaptive Takagi-Sugeno Fuzzy Model-Based Predictive Controller for Piezoelectric Actuators
Cheng, Long1,2; Liu, Weichuan1; Hou, Zeng-Guang1; Huang, Tingwen3; Yu, Junzhi1; Tan, Min1
Source PublicationIEEE TRANSACTIONS ON INDUSTRIAL ELECTRONICS
2017-04-01
Volume64Issue:4Pages:3048-3058
SubtypeArticle
AbstractPiezoelectric actuators (PEAs) are widely used in the nanopositioning applications due to their high stiffness, fast response, and ultrahigh precision. However, PEAs inherently have the hysteresis nonlinearity which can dramatically degrade the tracking performance. This paper proposes an adaptive Takagi-Sugeno (T-S) fuzzy model-based predictive controller with a parallel distributed control structure. Compared to the previous results, the proposed controller does not require the inverse hysteresis model of PEAs, and is easy to be calculated because the predictive subcontroller for each T-S fuzzy rule has an explicit form. Meanwhile, the parameters in the T-S fuzzy model can be online adjusted according to the real-time tracking error feedback, and the offline training accuracy of the T-S fuzzy model is no longer a serious concern. In addition, some physical constraints of the proposed controller can be well handled. To verify the proposed method, experiments are conducted on a commercial PEA product, and experiment results show that the proposed method has a satisfactory tracking performance. Furthermore, comparisons with some existing controllers are made and the proposed adaptive fuzzy model-based predictive controller outperforms these controllers.
KeywordAdaptive Fuzzy Modeling Hysteresis Model Predictive Control (Mpc) Parallel Distributed Control Piezoelectric Actuators (Peas)
WOS HeadingsScience & Technology ; Technology
DOI10.1109/TIE.2016.2644603
WOS KeywordTRACKING CONTROL ; HYSTERESIS ; SYSTEMS ; COMPENSATION ; IDENTIFICATION ; ROBUSTNESS ; INVERSE ; DESIGN ; STAGE
Indexed BySCI
Language英语
Funding OrganizationNational Natural Science Foundation of China(61422310 ; Beijing Natural Science Foundation(4162066) ; Qatar National Research Fund(NPRP 8-274-2-107) ; 61633016 ; 61370032 ; 61421004)
WOS Research AreaAutomation & Control Systems ; Engineering ; Instruments & Instrumentation
WOS SubjectAutomation & Control Systems ; Engineering, Electrical & Electronic ; Instruments & Instrumentation
WOS IDWOS:000397770200051
Citation statistics
Document Type期刊论文
Identifierhttp://ir.ia.ac.cn/handle/173211/14414
Collection复杂系统管理与控制国家重点实验室_先进机器人
Affiliation1.Chinese Acad Sci, Inst Automat, State Key Lab Management & Control Complex Syst, Beijing 100190, Peoples R China
2.Univ Chinese Acad Sci, Beijing 100049, Peoples R China
3.Texas A&M Univ Qatar, Doha 23874, Qatar
First Author AffilicationChinese Acad Sci, Inst Automat, State Key Lab Management & Control Complex Syst, Beijing 100190, Peoples R China
Recommended Citation
GB/T 7714
Cheng, Long,Liu, Weichuan,Hou, Zeng-Guang,et al. An Adaptive Takagi-Sugeno Fuzzy Model-Based Predictive Controller for Piezoelectric Actuators[J]. IEEE TRANSACTIONS ON INDUSTRIAL ELECTRONICS,2017,64(4):3048-3058.
APA Cheng, Long,Liu, Weichuan,Hou, Zeng-Guang,Huang, Tingwen,Yu, Junzhi,&Tan, Min.(2017).An Adaptive Takagi-Sugeno Fuzzy Model-Based Predictive Controller for Piezoelectric Actuators.IEEE TRANSACTIONS ON INDUSTRIAL ELECTRONICS,64(4),3048-3058.
MLA Cheng, Long,et al."An Adaptive Takagi-Sugeno Fuzzy Model-Based Predictive Controller for Piezoelectric Actuators".IEEE TRANSACTIONS ON INDUSTRIAL ELECTRONICS 64.4(2017):3048-3058.
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