@inproceedings{4d8035b421b34b62891399faa8be98ee,
title = "Model reference adaptive PID control of hydraulic parallel robot based on RBF neural network",
abstract = "In this paper, to improve the control performance of hydraulic parallel robot, we develop a model reference adaptive PID control based on radial basis function (RBF) neural network. To compensate for the asymmetry of the hydraulic actuator, we adopt model reference adaptive control strategy. Moreover, a RBF neural network is used to identify the hydraulic servo system on-line and then regulate the PID parameters on-line, which makes the system more adaptive. Simulation results show the controller has good tracking performance and good robustness, so the control strategy presented in this paper is effective.",
keywords = "Hydraulic actuator, Model reference adaptive PID control, Parallel robot, RBF neural network",
author = "Zhongcai Pei and Yanfang Zhang and Zhiyong Tang",
year = "2007",
doi = "10.1109/ROBIO.2007.4522366",
language = "英语",
isbn = "9781424417582",
series = "2007 IEEE International Conference on Robotics and Biomimetics, ROBIO",
publisher = "IEEE Computer Society",
pages = "1383--1387",
booktitle = "2007 IEEE International Conference on Robotics and Biomimetics, ROBIO",
address = "美国",
note = "2007 IEEE International Conference on Robotics and Biomimetics, ROBIO ; Conference date: 15-12-2007 Through 18-12-2007",
}