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Path Planning under Constraints and Path Following Control of Autonomous Underwater Vehicle with Dynamical Uncertainties and Wave Disturbances

机译:通过动力学不确定性和波击控制自动水下车辆的约束和路径下的路径规划

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摘要

The path planning and following control problems of autonomous underwater vehicle (AUV) in three-dimension (3D) are studied in this paper. In order to realize obstacle avoidance and path optimization, a path planning method based on particle swarm optimization (PSO) and cubic spline interpolation is developed. The curvature of the path obtained by this method is continuous, which can not only avoid obstacles but also meet the constraint of AUV's minimum radius of rotation. In the design of kinematics controller, an optimal guidance scheme based on model predictive control (MPC) is proposed, which takes into account the wave disturbances. Adaptive dynamical sliding mode control (ADSMC) technology is used to design dynamic controller, which can effectively overcome the influence of model uncertainties. In order to ensure the stability of the system, the stability condition of MPC is designed, and the stability of the closed-loop system is analyzed by applying cascade system theory. The control strategy proposed in this paper is compared with the line-of-sight (LOS) guidance through simulation experiment. The simulation results demonstrate that the proposed control strategy can not only improve the quality of path following, but also reduce the disturbance of waves, and thus is more conducive to energy saving.
机译:本文研究了三维(3D)中自主水下车辆(AUV)的路径规划和以下控制问题。为了实现避免障碍和路径优化,开发了一种基于粒子群优化(PSO)和立方样条插值的路径规划方法。通过该方法获得的路径的曲率是连续的,这不仅可以避免障碍物而且符合AUV的最小旋转半径的约束。在运动学控制器的设计中,提出了一种基于模型预测控制(MPC)的最佳指导方案,这考虑了波浪干扰。自适应动态滑模控制(ADSMC)技术用于设计动态控制器,可以有效地克服模型不确定性的影响。为了确保系统的稳定性,设计了MPC的稳定性条件,并通过应用级联系统理论来分析闭环系统的稳定性。本文提出的控制策略与通过仿真实验的视线(LOS)指导进行比较。仿真结果表明,所提出的控制策略不仅可以提高路径的质量,而且还可以减少波浪的干扰,因此更有利于节能。

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