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Robust adaptive precision motion control of hydraulic actuators with valve dead-zone compensation.
Deng, Wenxiang; Yao, Jianyong; Ma, Dawei.
Afiliação
  • Deng W; School of Mechanical Engineering, Nanjing University of Science and Technology, Nanjing 210094, China. Electronic address: wxdeng_njust@163.com.
  • Yao J; School of Mechanical Engineering, Nanjing University of Science and Technology, Nanjing 210094, China. Electronic address: jerryyao.buaa@gmail.com.
  • Ma D; School of Mechanical Engineering, Nanjing University of Science and Technology, Nanjing 210094, China. Electronic address: ma-dawei@163.com.
ISA Trans ; 70: 269-278, 2017 Sep.
Article em En | MEDLINE | ID: mdl-28760497
This paper addresses the high performance motion control of hydraulic actuators with parametric uncertainties, unmodeled disturbances and unknown valve dead-zone. By constructing a smooth dead-zone inverse, a robust adaptive controller is proposed via backstepping method, in which adaptive law is synthesized to deal with parametric uncertainties and a continuous nonlinear robust control law to suppress unmodeled disturbances. Since the unknown dead-zone parameters can be estimated by adaptive law and then the effect of dead-zone can be compensated effectively via inverse operation, improved tracking performance can be expected. In addition, the disturbance upper bounds can also be updated online by adaptive laws, which increases the controller operability in practice. The Lyapunov based stability analysis shows that excellent asymptotic output tracking with zero steady-state error can be achieved by the developed controller even in the presence of unmodeled disturbance and unknown valve dead-zone. Finally, the proposed control strategy is experimentally tested on a servovalve controlled hydraulic actuation system subjected to an artificial valve dead-zone. Comparative experimental results are obtained to illustrate the effectiveness of the proposed control scheme.
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Texto completo: 1 Base de dados: MEDLINE Idioma: En Ano de publicação: 2017 Tipo de documento: Article

Texto completo: 1 Base de dados: MEDLINE Idioma: En Ano de publicação: 2017 Tipo de documento: Article