Wheeled Robot Based on Fuzzy Neural Network Tracking Studies

Abstract:

The wheeled robot with non-integrity constraints is a typical nonlinear system, in order to achieve the ideal path tracing, presented a theory based on fuzzy neural network control. Centralized compensation system based on neural network uncertainty can be arbitrary-precision approximation of continuous nonlinear functions as well as the complex uncertainties with adaptive and learning ability. By MATLAB simulation showed that the control method to ensure fast convergence and error robustness of parameter uncertainties and external disturbance.

• Periodical: Applied Mechanics and Materials (Volumes 373-375)
• Pages: 181-184
• DOI: https://doi.org/10.4028/www.scientific.net/AMM.373-375.181
• Online since: August 2013
• Authors: Su Ying Zhang, Shao Jie Xu, Jing Fei Zhu, Bing Hao Li, Wen Pan Shi
• Keywords: Fuzzy Control, MATLAB Simulation, Neural Network (NN), Nonlinear System, Wheeled Robot

References

[1] Xuding Gong, Robot-controlled study, Zhejiang University Press, China, (2006).

[2] Yan Zhuang, Yue Sun, Wei Wang. Tracking control of nonholonomic mobile robot based on neural dynamics, Robot, Vol. 29, No. 5, pp.485-491, Feb. (2007).

DOI: 10.1109/wcica.2006.1713756

[3] Huixuan Fu, Hong Zhao, The application of MATLAB neural network design, China Mechine Press, China, (2010).

[4] Wei Shi, Zhengrong Xiang, Research on trajectory tracking control of wheeled robot, Nanjing University of Science & Technology, China, (2006).

[5] Xugang Feng, Real-time trajectory tracking of mobile robots based on Fuzzy Neural Network, METALLURGICAL POWER, Vol. 20, No. 5, pp.79-84, NOV. (2006).