AI 中文总结
针对质量分布动态变化的水面舰艇控制问题，提出基于质量分布控制的智能控制器，采用基于李雅普诺夫的非线性控制方案及人工神经网络估计相关动态和干扰，仿真验证该控制器能有效引导舰艇沿期望路径行驶且误差最小。
AI 中文摘要
解决质量分布动态变化的水面舰艇的控制和机动性问题仍然是一个悬而未决的问题。为解决该问题，我们提出一种用于水面舰艇路径跟踪问题的智能控制器，其通过质量分布进行控制，即一个控制输入是以质心为中心的。具体而言，我们开发了一种基于李雅普诺夫的非线性控制方案，使无人舰艇能根据视线引导律跟踪平滑路径。控制输入包括向前运动的推力和移动系统整体质量分布的滑动质量的位置。采用人工神经网络估计未建模动态和外部干扰。仿真结果证明了所提控制器能以最小误差引导舰艇沿期望路径行驶的有效性。
英文摘要
Addressing the control and maneuverability of surface vehicles with dynamically changing mass distributions is still an open problem. To solve the problem, we propose an intelligent controller for the path-following problem of a surface vehicle, which is controlled through mass distribution. This means that one of the control inputs is mass-centric. Specifically, we developed a Lyapunov-based nonlinear control scheme to enable an unmanned vessel to follow a smooth path according to a line-of-sight guidance law. The control inputs consist of the thrust force for forward motion and the position of a sliding mass that shifts the system's overall mass distribution. Artificial neural networks are employed to estimate unmodeled dynamics and external disturbances. Simulation results demonstrate the effectiveness of the proposed controller in guiding the vessel along the desired path with minimal error.
CommentsThis paper is part of the European Control Conference - ECC 2026 proceedings (https://ecc26.euca-ecc.org/)
