Title :
Sliding Mode Control of Flexible Joint Using Gaussian Radial Basis Function Neural Networks
Author :
Farivar, F. ; Shoorehdeli, M. Aliyari ; Nekoui, M.A. ; Teshnehlab, M.
Author_Institution :
Dept. of Mechatron. Eng., Islamic Azad Univ., Tehran
Abstract :
This paper, describes a hybrid control method to control a flexible joint. Dynamic equation of the system has been derived. The designed controllers consist of two parts: classical controller, which is a Linear Quadratic Regulation (LQR), and a hybrid controller,utilizing sliding mode control using Gaussian Radial Basis Function Neural Networks (RBFNN). The RBFNN is trained during the control process and it is not necessary to be trained off-line.
Keywords :
Gaussian processes; flexible manipulators; radial basis function networks; variable structure systems; Gaussian radial basis function neural networks; dynamic equation; flexible joint; hybrid controller; linear quadratic regulation; sliding mode control; Computer networks; Control systems; Damping; Manipulator dynamics; Nonlinear equations; Orbital robotics; Radial basis function networks; Robot control; Sliding mode control; Symmetric matrices; Flexible joint; Hybrid control; Radial basis function neural network; Sliding mode; Sliding surface;
Conference_Titel :
Computer and Electrical Engineering, 2008. ICCEE 2008. International Conference on
Conference_Location :
Phuket
Print_ISBN :
978-0-7695-3504-3
DOI :
10.1109/ICCEE.2008.131
