Moving-Horizon Estimation and Nonlinear Model Predictive Control of Cable-Driven Soft Manipulators

2026-07-27

AI Summary

This work addresses the challenge of achieving high-precision control in cable-driven soft robotic arms, which stems from the absence of accurate yet computationally efficient models. To overcome this, the authors propose a smooth dynamics modeling approach that operates without direct tension sensing. Building upon a simplified Cosserat rod theory, the method treats cable lengths as direct inputs and explicitly approximates the complementarity between cable tension and slack. By integrating moving horizon estimation (MHE) with nonlinear model predictive control (NMPC), the framework unifies state estimation and task-space control within a single architecture. Simulations and experiments on a four-cable prototype demonstrate that the proposed approach enables real-time execution while significantly improving end-effector position tracking accuracy and shape regulation capability.

Abstract

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.

Problem

• soft manipulators
• cable-driven
• state estimation
• task-space control
• model-based control

Innovation

• Moving-Horizon Estimation
• Nonlinear Model Predictive Control
• Cosserat-rod model
• Cable-driven soft manipulator
• Cable-length control