Underactuated UUV tracking control of adaptive RBF neural network and backstepping method

作者：Zhang, Wei^*; Teng, Yanbin; Wei, Shilin; Hu, Shouyi; Zhang, Ji'nan

来源：Journal of Harbin Engineering University, 2018, 39(1): 93-99.

DOI：10.11990/jheu.201611010

• Adaptive Control
• Multi-disturbance
• RBF Neural Network
• Robust
• Time-varing perturbation
• Trajectory tracking
• Underwater unmanned vehicles

An underwater unmanned vehicle (UUV) model has an error that causes time-varying perturbation in the fluid. Therefore, the radial basis RBF) neural network control technique was introduced in order to carry out an adaptive compensation estimate. Additionally, the backstepping method was utilized in order to design the position, attitude, and velocity controller of the UUV. Virtual speed was used in order to replace the attitude error for the purpose of converting the attitude tracking control to speed control. The simulation results show that this method was effective in improving the robustness and adaptability of the UUV.

• 出版日期2018
• 单位哈尔滨工程大学