Title :
Neuro-fuzzy network control for a mobile robot
Author :
Jun Oh Jang ; Hee Tae Chung
Author_Institution :
Uiduk Univ., Kyongju, South Korea
Abstract :
A control structure that makes possible the integration of a kinematic controller and a neuro-fuzzy network (NFN) dynamic controller for mobile robots is presented. A combined kinematic/dynamic control law is developed using backstepping and stability is guaranteed by Lyapunov theory. The NFN controller proposed in this work can deal with unmodeled bounded disturbances and/or unstructured unmodeled dynamic in the mobile robot. On-line NFN parameter tuning algorithms do no require off-line learning yet guarantee small tracking errors and bounded control signals are utilized.
Keywords :
Lyapunov methods; feedback; fuzzy control; mobile robots; neurocontrollers; robot kinematics; stability; Lyapunov stability; backstepping; feedback control; kinematic controller; mobile robot; neuro-fuzzy network control; stability; Actuators; Friction; Fuzzy neural networks; Kinematics; Mechanical systems; Mobile robots; Nonlinear dynamical systems; Trajectory; Vehicle dynamics; Wheels; Feedback control; Lyapunov stability; Mobile robot; Neuro-fuzzy networks;
Conference_Titel :
American Control Conference, 2009. ACC '09.
Conference_Location :
St. Louis, MO
Print_ISBN :
978-1-4244-4523-3
Electronic_ISBN :
0743-1619
DOI :
10.1109/ACC.2009.5159871