AI 中文总结
针对电缆驱动软机械手精确控制难的问题，提出基于简化柯塞尔动力学的MHE和NMPC框架，开发电缆长度驱动建模公式，引入MHE方法和NMPC控制器，经模拟和实验验证，可实时实现并精确跟踪末端执行器位置。
AI 中文摘要
由于难以开发出准确且计算易处理的模型用于基于模型的估计和控制，软机械手的精确控制仍具有挑战性。简化的柯塞尔杆模型为软机器人动力学提供了基于物理和面向控制的描述。本文提出了一种基于简化柯塞尔动力学的电缆驱动软机械手的移动时域估计（MHE）和非线性模型预测控制（NMPC）框架。通过近似电缆张力和电缆松弛之间的互补关系，开发了一种平滑的电缆长度驱动建模公式，实现无直接张力传感的电缆长度控制。基于此公式，引入MHE方法估计简化状态并从末端执行器姿态测量和电缆长度信息重建机械手配置。然后制定NMPC控制器以在电缆长度和电缆速率约束下实现任务空间控制。通过数值模拟和实验验证了该框架。模拟结果证明了估计器和控制器在多电缆软机械手姿态和应变相关调节方面的有效性。四电缆原型的实验结果进一步表明，所提出的MHE-NMPC方案可实时实现，并通过电缆长度控制实现精确的末端执行器位置跟踪。
英文摘要
Precise control of soft manipulators remains challenging due to the difficulty of developing accurate yet computationally tractable models for model-based estimation and control. Reduced Cosserat-rod models provide a physics-based and control-oriented description of soft-robot dynamics, offering an explicit alternative to purely data-driven input-output representations. In this paper, we propose a moving-horizon estimation (MHE) and nonlinear model predictive control (NMPC) framework for cable-driven soft manipulators based on reduced Cosserat dynamics. A smooth cable-length-driven modeling formulation is developed by approximating the complementarity relationship between cable tension and cable slackness, enabling cable-length control without direct tension sensing. Based on this formulation, an MHE method is introduced to estimate the reduced state and reconstruct the manipulator configuration from end-effector pose measurements and cable-length information. An NMPC controller is then formulated to achieve task-space control under cable-length and cable-rate constraints. The proposed framework is validated through numerical simulations and experiments. Simulation results demonstrate the effectiveness of the estimator and controller for pose and strain-related regulation on a multi-cable soft manipulator. Experimental results on a four-cable prototype further show that the proposed MHE-NMPC scheme can be implemented in real time and enables accurate end-effector position tracking through cable-length control.
