首页> 外文OA文献 >GLOBALLY STABLE ADAPTIVE DYNAMIC SURFACE CONTROL FOR COOPERATIVE PATH FOLLOWING OF MULTIPLE UNDERACTUATED AUTONOMOUS UNDERWATER VEHICLES
【2h】

GLOBALLY STABLE ADAPTIVE DYNAMIC SURFACE CONTROL FOR COOPERATIVE PATH FOLLOWING OF MULTIPLE UNDERACTUATED AUTONOMOUS UNDERWATER VEHICLES

机译:多个欠驱动自动水下车辆的合作路径跟随的全局稳定自适应动力表面控制

摘要

The cooperative path following problem of multiple underactuated autonomous underwater vehicles (AUVs) involves two tasks. The first one is to force each AUV to converge to the desired parameterized path. The second one is to satisfy the requirement of a cooperative behavior along the paths. In this paper, both of the tasks have been further studied. For the first one, a simplified path following controller is proposed by incorporating the dynamic surface control (DSC) technique to avoid the calculation of derivatives of virtual control signals. Besides, in order to handle the uncertain dynamics, a new type of neural network (NN) adaptive controller is derived, and then an NN based energy efficient path following controller is firstly proposed, which consists of an adaptive neural controller dominating in the neural active region and an extra robust controller working outside the neural active region. For the second one, in order to reduce the amount of communications between multiple AUVs, a distributed estimator for the reference common speed is firstly proposed as determined by the communications topology adopted, which means the global knowledge of the reference speed is relaxed for the problem of cooperative path following. The overall algorithm ensures that all the signals in the closed-loop system are globally uniformly ultimately bounded (GUUB) and the output of the system converges to a small neighborhood of the reference trajectory by properly choosing the design parameters. Simulation results validate the performance and robustness of the proposed strategy.
机译:多个欠驱动自动水下航行器(AUV)的协作路径跟随问题涉及两个任务。第一个是迫使每个AUV收敛到所需的参数化路径。第二个是满足沿着路径的协作行为的要求。在本文中,这两个任务已得到进一步研究。对于第一个,通过结合动态表面控制(DSC)技术,提出了一种简化的路径跟随控制器,以避免计算虚拟控制信号的导数。此外,为了处理不确定的动力学问题,推导了一种新型的神经网络自适应控制器,然后提出了一种基于神经网络的能量有效路径跟随控制器,该控制器由以神经活动为主的自适应神经控制器组成。区域和在神经活动区域之外工作的额外鲁棒控制器。对于第二种方法,为了减少多个AUV之间的通信量,首先根据所采用的通信拓扑确定参考公共速度的分布式估计器,这意味着该问题对于参考速度的全局知识是放宽的合作路径跟踪。整体算法可确保闭环系统中的所有信号全局统一最终有界(GUUB),并且通过适当选择设计参数,系统的输出收敛到参考轨迹的一小部分。仿真结果验证了所提出策略的性能和鲁棒性。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利

客服邮箱:kefu@zhangqiaokeyan.com

京公网安备:11010802029741号 ICP备案号:京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有
  • 客服微信

  • 服务号