Adaptive Tracking Control of Underactuated USV Based on Back-stepping and RBF Neural Network

作者：Li, Yanzhe; Pan, Feng; Xing, Yao

来源：9th International Conference on Intelligent Control and Information Processing, ICICIP 2018, 2018-11-09 To 2018-11-11.

DOI：10.1109/ICICIP.2018.8606718

• Back-stepping method
• High
• gain observers
• RBF Neural Network
• Trajectory tracking
• Underactuated

In order to solve the problem of trajectory tracking control of unmanned surface vehicles (USV) with unknown speed information, an adaptive control algorithm based on Radial Basis RBF) neural network and back-stepping method is proposed. This algorithm uses the back-stepping method to design an easy-to-implement control input based on the model parameters, uses the high-gain observer to estimate the speed information, and uses the RBF neural network to estimate the model parametric uncertainties and the environmental disturbances such as wind and wave. Then the control law and the weight update law of RBF neural network are designed. Finally, the systemic stability is proved by Lyapunov function. Simulational experiments and physical experiments verify the feasibility and effectiveness of this algorithm.

• 出版日期2018
• 单位西北工业大学