Model reference adaptive PID control of hydraulic parallel robot based on RBF neural network

Author

Pei, Zhongcai ; Zhang, Yanfang ; Tang, Zhiyong

Author_Institution

Sch. of Autom. Sci. & Electr. Eng., BeiHang Univ., Beijing

fYear

2007

fDate

15-18 Dec. 2007

Firstpage

1383

Lastpage

1387

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 actuators; model reference adaptive control systems; neurocontrollers; radial basis function networks; robots; robust control; servomechanisms; three-term control; RBF neural network; hydraulic actuator; hydraulic parallel robot; hydraulic servosystem; model reference adaptive PID control; radial basis function neural network; Adaptive control; Control systems; Hydraulic actuators; Neural networks; Parallel robots; Programmable control; Robotics and automation; Servomechanisms; Three-term control; Valves; Parallel robot; RBF neural network; hydraulic actuator; model reference adaptive PID control;

fLanguage

English

Publisher

ieee

Conference_Titel

Robotics and Biomimetics, 2007. ROBIO 2007. IEEE International Conference on

Conference_Location

Sanya

Print_ISBN

978-1-4244-1761-2

Electronic_ISBN

978-1-4244-1758-2

Type

conf

DOI

10.1109/ROBIO.2007.4522366

Filename

4522366