Inductance-Based Force Self-Sensing in Fiber-Reinforced Pneumatic Twisted-and-Coiled Actuators

2026-03-19

AI Summary

This work addresses the challenge of achieving high-precision closed-loop control in fiber-reinforced pneumatic helical actuators, which suffer from strong hysteresis and a lack of intrinsic sensing capability. To overcome these limitations, the authors innovatively embed conductive nickel wires within the actuator to enable self-sensing of force through inductance signals, from which displacement is indirectly inferred. A parametric inductance–force model is developed and integrated with an extended Kalman filter and constrained optimization to construct a nonlinear hybrid observer that effectively mitigates ambiguity in the inductance–force mapping and compensates for hysteresis effects. Experimental results demonstrate that the proposed approach achieves force estimation accuracy comparable to that of external force sensors across varying loads, significantly enhancing the actuator’s proprioceptive capability and control robustness.

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Abstract

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.

Problem

• hysteresis
• proprioception
• closed-loop control
• force estimation
• pneumatic actuators

Innovation

• inductance-based self-sensing
• fiber-reinforced pneumatic actuator
• force estimation
• Extended Kalman Filter
• hysteresis reduction