Observer-based adaptive neural sliding mode trajectory tracking control for remotely operated vehicles with thruster constraints
Observer-based adaptive neural sliding mode trajectory tracking control for remotely operated vehicles with thruster constraints
复制标题
基于观测器的带推进器约束的遥控飞行器自适应神经滑模轨迹跟踪控制
DOI：
10.1177/01423312211004819
复制
发表时间：
2021-04-19
影响因子：
1.8
通讯作者：
Zhang, Mingjun
中科院分区：
文献类型：
--
作者：
Chu, Zhenzhong;Chen, Yunsai;Zhang, Mingjun
针对一类具有推进器约束、状态不可测和未知非线性的遥控飞行器(ROV)系统，讨论了其轨迹跟踪控制问题。用径向基函数(RBF)神经网络逼近未知的非线性函数。设计了一种基于神经网络的自适应状态观测器，并对不可测状态进行了估计。针对推进器饱和约束问题，设计了饱和补偿辅助系统，并根据辅助系统状态构造了饱和因子。应用反推设计方法，设计了一种自适应神经滑模轨迹跟踪控制器，其中自适应律包含饱和因子。证明了轨迹跟踪误差的一致最终有界(UUB)。最后，通过仿真验证了该轨迹跟踪控制方法的有效性。
For a class of remotely operated vehicle (ROV) systems with thruster constraints, immeasurable states, and unknown nonlinearities, the trajectory tracking control problem was discussed in this paper. The unknown nonlinear functions were approximated by radial basis function (RBF) neural networks. An adaptive state observer based on neural networks was designed and the immeasurable states were estimated. Considering the problem of thruster saturation constraints, an auxiliary system for saturation compensation was designed and a saturation factor was constructed by the auxiliary system state. By applying the backstepping design method, an adaptive neural sliding mode trajectory tracking controller was developed, in which the saturation factor is contained in adaptive laws. It was proved that the uniformly ultimately bounded (UUB) of trajectory tracking errors can be obtained. Finally, the effectiveness of the proposed trajectory tracking control approach was checked by simulations.