Submitted:
14 October 2026
Posted:
15 October 2026
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Abstract
Presliding friction in ball-screw drives produces multivalued force–displacement hysteresis. This study uses a normalized path coordinate u to represent an ordered cycle through the single-valued mappings x(u) and Feq(u), where Feq is the motor-equivalent axial force. Four first-order Takagi–Sugeno fuzzy architectures are compared using a 600-point F200, 0.5 Hz experimental loop. Across ten leakage-controlled 70/30 train–test partitions, SC16–TS achieved the lowest mean test NRMSE among the fuzzy models (0.01054), closely followed by ANFIS–TS (0.01073), with no significant difference after multiplicity correction (p=0.064). Leave-one-complicate-cycle-out validation yielded mean NRMSEs of 0.01312 and 0.01357, respectively. A same-input RBF–SVR benchmark achieved a slightly lower NRMSE of 0.01028, whereas the fuzzy models retained explicit local rule bases. FCM–TS showed the greatest robustness under stronger synthetic training-noise contamination. Phase-aligned transfer from 0.5 to 1.0 Hz increased NRMS E to approximately 0.034 and loop-area error to approximately 25%, demonstrating that the normalized path coordinate alone does not capture frequency-dependent changes in the hysteretic response. Overall, normalized-path fuzzy modeling provides an accurate and interpretable representation of experimental presliding history while identifying the need for an explicit frequency-aware state for cross-condition prediction.
Keywords:
presliding friction
; ball-screw drive
; friction hysteresis
; path parameterization
; Takagi–Sugeno fuzzy systems
; ANFIS
; cross-cycle validation
; frequency transfer
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