Adaptive Neural Network Path Tracking of Unmanned Ground Vehicle

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• 作者：Xiaohong Liao ; Zhao Sun ; Liguo Weng ; Bin Li ; Yongduan Song ; et al.
• 刊名：Lecture Notes in Computer Science
• 出版年：2006
• 出版时间：2006
• 年：2006
• 卷：3972
• 期：1
• 页码：pp.1233-1238
• 全文大小：228 KB

文摘

Unmanned ground vehicles (UGVs) play an increasingly important role in future space exploration and battlefield. This work is concerned with the automatic path tracking control of UGVs. By using the structure properties of the system, neuro-adaptive control algorithms are developed for high precision tracking without involving complex design procedures – the proposed control scheme only demands partial information of the system, no detail description of the system model is needed. Furthermore, uncertain effects such as external disturbance and uncertain parameters can easily be handled. In addition, all the internal signals are uniformly bounded and the control torque is smooth anywhere.