哈尔滨工程大学学报2018，Vol.39Issue(1)：93-99,7.DOI:10.11990/jheu.201611010
欠驱动UUV自适应RBF神经网络反步跟踪控制
Underactuated UUV tracking control of adaptive RBF neural network and backstepping method
摘要
Abstract
An underwater unmanned vehicle ( UUV) model has an error that causes time-varying perturbation in the fluid.Therefore, the radial basis function ( 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.关键词
反步法/自适应RBF神经网络/水下无人航行器/轨迹跟踪/多扰动/自适应控制/鲁棒性/时变扰动Key words
backstepping/adaptive RBF neural network/underwater unmanned vehicle ( UUV)/trajectory track-ing/multi-disturbance/adaptive control/robust/time-varing perturbation分类
信息技术与安全科学引用本文复制引用
张伟,滕延斌,魏世琳,胡守一,张吉楠..欠驱动UUV自适应RBF神经网络反步跟踪控制[J].哈尔滨工程大学学报,2018,39(1):93-99,7.基金项目
国家自然科学基金项目( E091002/51309067 ) （ E091002/51309067 ）
黑龙江省科学基金项目(E2016020) （E2016020）
中央高校基本科研业务费专项基金资助(HEUCF201736,HEUCFM171011). （HEUCF201736,HEUCFM171011）
