提出统一控制框架，让人工肌肉独立调节力矩与刚度。
Decoupling Torque and Stiffness: A Unified Modeling and Control Framework for Antagonistic Artificial Muscles
- 用分离式帕德模型和双状态动态封装，实现多类人工肌肉统一建模。
- 控制周期小于1毫秒，支持力矩与刚度独立跟踪，刚度切换时力矩不变。
- 基于穿透深度自适应调节刚度，适合动态交互场景的机器人设计。
拮抗式人工肌肉可解耦关节力矩与刚度，但接触瞬态常破坏这种独立性。本文提出一个适用于气动、电液及介电弹性体人工肌肉家族的统一实时控制框架：包含可分离的帕德力模型与最小双状态动态封装，级联逆动力学控制器采用共收缩/偏置坐标，以及基于生物启发的深度自适应交互策略，根据穿透深度调度刚度。控制器每周期运行时间低于1毫秒，在固定力矩下完成刚度阶跃测试时仍保持力矩调控稳定。在软到硬环境耦合阻抗接触协议仿真中，对比深度自适应刚度与固定刚度基线，揭示了冲击承受能力与稳定性之间的权衡。结果为肌骨骼拮抗机器人在动态交互中实现自适应阻抗行为提供了控制基础。
原文摘要 · Abstract (English)
Antagonistic artificial muscles can decouple joint torque and stiffness, but contact transients often degrade this independence. We present a unified real-time framework applicable across pneumatic, electrohydraulic, and dielectric elastomer artificial muscle families: a separable Padé force model with a minimal two-state dynamic wrapper, a cascaded inverse-dynamics controller in co-contraction/bias coordinates, and a bio-inspired depth-adaptive interaction policy that schedules stiffness based on penetration depth. The controller runs in under 1 ms per control tick and demonstrates independent torque and stiffness tracking, including a fixed-torque stiffness-step test that preserves torque regulation through stiffness transitions. In a coupled impedance contact protocol simulated across soft-to-rigid environments, comparing depth-adaptive stiffness to fixed-stiffness baselines reveals a shock/load versus stability tradeoff. These results provide a control-oriented foundation for musculoskeletal antagonistic robots to execute adaptive impedance behaviors in dynamic interactions.
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