Title :
Application of Fault Tolerant Controller Based on RBF Neural Networks for Mobile Robot
Author_Institution :
Sch. of Electr. Eng. & Inf. Sci., Hebei Univ. of Sciennce & Technol., Shijiazhuang, China
Abstract :
This paper presents a method based on RBF neural networks for achieving fault tolerant control in the mobile robot control scheme. Tuning rules of the RBF networks which guarantees the stability of the fault system were derived and the on-line fault tolerant control scheme was developed. The method does not need fault detection and diagnosis modules. As an example of the application, a tracking control problem for the speed and azimuth of a mobile robot driven by two independent wheels is solved by using the controller. The effectiveness of the proposed method is illustrated by performing the simulation of a circular trajectory tracking control.
Keywords :
fault diagnosis; fault tolerance; intelligent robots; mobile robots; neurocontrollers; stability; RBF neural network; fault detection; fault diagnosis module; fault system; fault tolerant control; mobile robot; trajectory tracking control; Control systems; Fault detection; Fault diagnosis; Fault tolerance; Fault tolerant systems; Mobile robots; Neural networks; Radial basis function networks; Robot control; Stability; RBF networks; fault tolerant control; mobile robot;
Conference_Titel :
Intelligent Ubiquitous Computing and Education, 2009 International Symposium on
Conference_Location :
Chengdu
Print_ISBN :
978-0-7695-3619-4
DOI :
10.1109/IUCE.2009.140
