This paper presents an advanced bio-inspired control framework for cable-driven parallel robots (CDPRs), based on the principle of agonist–antagonist biomechanical coordination specific to the human muscular system. The proposed architecture introduces a variable stiffness regulation strategy, in which cable tensions are dynamically adjusted so as to reproduce the contraction and relaxation behaviors specific to myofibrillar structures. The control model employs a deterministic mechanical adaptation law, formulated in terms of positional deviation and force variation, through which the equivalent stiffness of the system can adjust itself in real time, without depending on empirical models or machine learning algorithms. The experimental validation was performed on a CDPR platform with eight redundant cables, configured for full-scope simulations and laboratory tests in the hardware-in-the-loop (HIL) mode. The experiments included controlled interactions with a biomechanical phantom designed to reproduce the elastic properties of biological tissues, allowing for the precise assessment of the stability, precision, and dynamic behavior of the system. The obtained results include a 2.6 mm RMS error in trajectory tracking and a maximum contact force below 25 N, indicating a stable, safe, and adaptive operating regime. The integration of biomechanical principles into the control architecture of cable-driven parallel robots points the way towards a new generation of intelligent actuator systems, capable of combining mechanical precision with structural adaptability, ensuring remarkable application perspectives in the fields of rehabilitation robotics, delicate manipulation, and collaborative robotics.
Cable-actuated parallel robots, Bio-inspired control, Variable stiffness control, Mechanical safety, Adaptive control, Full-scope simulation, Conformal robotics.
Dragos Mihai PANAGORET, Andreea Anamaria PANAGORET, Olivia-Roxana ALECSOIU, Maria Felicia CHIRCULESCU, Adina-Milena TATAR, "Bio-Inspired Stiffness Control for Cable-Driven Parallel Robots", Studies in Informatics and Control, ISSN 1220-1766, vol. 35(2), pp. 97-110, 2026. https://doi.org/10.24846/v35i2y202609
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