Fiber-reinforced pneumatic twisted-and-coiled actuators (FR-PTCAs) offer high power density and compliance but their strong hysteresis and lack of intrinsic proprioception limit effective closed-loop control. This paper presents a self-sensing FR-PTCA integrated with a conductive nickel wire that enables intrinsic force estimation and indirect displacement inference via inductance feedback. Experimental characterization reveals that the inductance of the actuator exhibits a deterministic, low-hysteresis inductance-force relationship at constant pressures, in contrast to the strongly hysteretic inductance-length behavior. Leveraging this property, this paper develops a parametric self-sensing model and a nonlinear hybrid observer that integrates an Extended Kalman Filter (EKF) with constrained optimization to resolve the ambiguity in the inductance-force mapping and estimate actuator states. Experimental results demonstrate that the proposed approach achieves force estimation accuracy comparable to that of external load cells and maintains robust performance under varying load conditions.

翻译：纤维增强气动扭卷致动器（FR-PTCAs）具有高功率密度和柔顺性，但其显著的迟滞效应和缺乏固有本体感觉限制了其有效的闭环控制。本文提出一种集成导电镍线的自感知FR-PTCA，通过电感反馈实现内禀力估计与间接位移推断。实验表征表明，在恒定压力条件下，该致动器的电感呈现出确定性的低迟滞电感-力关系，这与具有显著迟滞特性的电感-长度行为形成鲜明对比。利用这一特性，本文构建了参数化自感知模型和非线性混合观测器，该观测器通过扩展卡尔曼滤波（EKF）与约束优化相结合的方法，解决了电感-力映射中的歧义性并实现了致动器状态估计。实验结果表明，所提方法获得的力估计精度可与外部负载传感器相媲美，并在多变负载条件下保持稳健性能。