CASIA OpenIR  > 复杂系统管理与控制国家重点实验室  > 先进机器人
An Inversion-free Model Predictive Control with Error Compensation for Piezoelectric Actuators
Liu WC(刘伟川); Cheng L(程龙); Hou ZG(侯增广); Tan M(谭民); long cheng
2015
Conference Name2015 American Control Conference
Source Publication2015 American Control Conference
Conference DateJuly 1-3, 2015
Conference PlaceChicago, IL, USA
Abstract
This paper addresses an inversion-free model
predictive control with error compensation for piezoelectric
actuators (PEAs), which is based on a dynamic linearized
multi-layer feedforward neural network model. By the proposed
method, the inverse model of the inherent hysteresis in PEAs
is not required, and the control law can be obtained in an
explicit form. By using the technique of constrained quadratic
programming, the proposed method still works well when
dealing with the plant physical constraints. Moreover, an
error compensation term is introduced into the control law to
attenuate the steady-state error. To verify the effectiveness of the
proposed method, experiments are conducted on a commercial
PEA. The experiment results show that the proposed method
has a good tracking performance for PEAs.
KeywordHysteresis Neural Network Modeling Dynamic Linearization Model Predictive Control Piezoelectric Actuators
Document Type会议论文
Identifierhttp://ir.ia.ac.cn/handle/173211/11666
Collection复杂系统管理与控制国家重点实验室_先进机器人
Corresponding Authorlong cheng
Recommended Citation
GB/T 7714
Liu WC,Cheng L,Hou ZG,et al. An Inversion-free Model Predictive Control with Error Compensation for Piezoelectric Actuators[C],2015.
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