Neural-Network-Based Nonlinear Model Predictive Control for Piezoelectric Actuators

CORC > 自动化研究所 > 中国科学院自动化研究所 > 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

	Neural-Network-Based Nonlinear Model Predictive Control for Piezoelectric Actuators
	Cheng, Long; Liu, Weichuan; Hou, ZengGuang; Yu, Junzhi; Tan, Min
刊名	IEEE TRANSACTIONS ON INDUSTRIAL ELECTRONICS
	2015-12-01
卷号	62 期号:12 页码:7717-7727
关键词	Neuralnetworks nonlinearautoregressive-moving-average with exogenous inputs (NARMAX) piezoelectric actuator (PEA) predictive control
通讯作者	Cheng, Long
英文摘要	Piezoelectric actuators (PEAs) have been widely used in nanotechnology due to their characteristics of fast response, large mass ratio, and high stiffness. However, hysteresis, which is an inherent nonlinear property of PEAs, greatly deteriorates the control performance of PEAs. In this paper, a nonlinear model predictive control (NMPC) approach is proposed for the displacement tracking problem of PEAs. First, a "nonlinear autoregressive-moving-average with exogenous inputs" (NARMAX) model of PEAs is implemented by multilayer neural networks; second, the tracking controlproblem is converted into an optimization problem by the principle of NMPC, and then, it is solved by the Levenberg-Marquardt algorithm. The most distinguished feature of the proposed approach is that the inversion model of hysteresis is no longer a necessity, which avoids the inversion imprecision problem encountered in the widely used inversion-based control algorithms. To verify the effectiveness of the proposed modeling and control methods, experiments are made on a commercial PEA product (P-753.1CD, Physik Instrumente), and comparisons with some existing controllers and a commercial proportional-integral-derivative controller are conducted. Experimental results show that the proposed scheme has satisfactory modeling and control performance.
WOS标题词	Science & Technology ; Technology
类目[WOS]	Automation & Control Systems ; Engineering, Electrical & Electronic ; Instruments & Instrumentation
研究领域[WOS]	Automation & Control Systems ; Engineering ; Instruments & Instrumentation
关键词[WOS]	PIEZOCERAMIC ACTUATOR ; INVERSE-FEEDFORWARD ; TRACKING CONTROL ; PREISACH MODEL ; HYSTERESIS ; COMPENSATION ; IDENTIFICATION
收录类别	SCI
语种	英语
WOS记录号	WOS:000365019500040
内容类型	期刊论文
源URL	[http://ir.ia.ac.cn/handle/173211/10517]
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
作者单位	State Key Laboratory of Management and Control for Complex Systems, Institute of Automation, Chinese Academy of Sciences, Beijing, China
推荐引用方式 GB/T 7714	Cheng, Long,Liu, Weichuan,Hou, ZengGuang,et al. Neural-Network-Based Nonlinear Model Predictive Control for Piezoelectric Actuators[J]. IEEE TRANSACTIONS ON INDUSTRIAL ELECTRONICS,2015,62(12):7717-7727.
APA	Cheng, Long,Liu, Weichuan,Hou, ZengGuang,Yu, Junzhi,&Tan, Min.(2015).Neural-Network-Based Nonlinear Model Predictive Control for Piezoelectric Actuators.IEEE TRANSACTIONS ON INDUSTRIAL ELECTRONICS,62(12),7717-7727.
MLA	Cheng, Long,et al."Neural-Network-Based Nonlinear Model Predictive Control for Piezoelectric Actuators".IEEE TRANSACTIONS ON INDUSTRIAL ELECTRONICS 62.12(2015):7717-7727.