제어로봇시스템학회:학술대회논문집
- 2005.06a
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- Pages.330-333
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- 2005
Neurointerface Using an Online Feedback-Error Learning Based Neural Network for Nonholonomic Mobile Robots
- Lee, Hyun-Dong (Department of Advanced Systems Control Eng., Graduate School of Science and Engineering, Saga University) ;
- Watanabe, Keigo (Department of Advanced Systems Control Eng., Graduate School of Science and Engineering, Saga University) ;
- Jin, Sang-Ho (Department of Mechanical Engineering, Doowon Technical College) ;
- Syam, Rafiuddin (Department of Advanced Systems Control Eng., Graduate School of Science and Engineering, Saga University) ;
- Izumi, Kiyotaka (Department of Advanced Systems Control Eng., Graduate School of Science and Engineering, Saga University)
- Published : 2005.06.02
Abstract
In this study, a method of designing a neurointerface using neural network (NN) is proposed for controlling nonholonomic mobile robots. According to the concept of virtual master-slave robots, in particular, a partially stable inverse dynamic model of the master robot is acquired online through the NN by applying a feedback-error learning method, in which the feedback controller is assumed to be based on a PD compensator for such a nonholonomic robot. A tracking control problem is demonstrated by some simulations for a nonholonomic mobile robot with two-independent driving wheels.
Keywords