Open AccessModel identification and parametric adaptive control of hydraulic manipulator with neighborhood field optimization
Author(s) -
Guo Qing,
Chen Zhenlei,
Shi Yan,
Liu Gan
Publication year - 2021
Publication title -
iet control theory and applications
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.059
H-Index - 108
eISSN - 1751-8652
pISSN - 1751-8644
DOI - 10.1049/cth2.12145
Subject(s) - control theory (sociology) , controller (irrigation) , backstepping , parametric statistics , torque , system identification , parametric model , actuator , engineering , computer science , adaptive control , control engineering , mathematics , control (management) , data modeling , statistics , physics , software engineering , artificial intelligence , agronomy , biology , thermodynamics , electrical engineering
The model identification and uncertain parameters estimation are common control problems in multi‐DOF manipulator system, since both model parametric uncertainties and unknown external disturbance often degrade the output performance and the close‐loop system stability. In this study, by using the joint angle and the torque information, a neighborhood field optimization is adopted to identify the Lagrange model parameters of two‐DOF hydraulic manipulator. The fitness function of the neighborhood field optimization is designed to optimize the minimal squared error of the torque estimation and to obtain the lumped estimated parameters with high accuracy. Then based on the identification model, a parametric adaptive controller is designed to address uncertain electro‐hydraulic parameters and external disturbances. Furthermore, a new stable control variable is redesigned to avoid the redundant input saturation of electro‐hydraulic actuator. The effectiveness of the proposed controller is verified by the comparative experimental results with the general backstepping controller.