ArticleBioengineering (Basel, Switzerland)2026
Evaluation of a Fuzzy-Supervised PID Controller for a Parallel Rehabilitation Mechanism.
Article in Bioengineering (Basel, Switzerland), 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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Abstract
Accurate actuator-space tracking is an important engineering requirement for repeatable motion delivery by parallel rehabilitation mechanisms, but controller performance should also be assessed under configuration-dependent dynamics and modeling uncertainty. This study evaluates a bounded fuzzy-supervised proportional-integral-derivative (FSPID) controller for a three-chain 3STC+S parallel rehabilitation mechanism. CAD-derived inverse kinematics generated the three prismatic-joint reference trajectories, while closed-loop behavior was simulated using a Simscape Multibody model including rigid-body mass and inertia properties, gravity, closed-loop constraints, and external force/moment loading. Three fixed-gain PID loops formed the baseline. The FSPID supervisor used zero-order Sugeno inference to adjust proportional and derivative gains within prescribed bounds, while the integral action remained fixed and was implemented with a leaky integrator. Under the nominal 1° trajectory at 0.2 Hz, FSPID reduced mean root-mean-square error (RMSE), maximum absolute error, and integral absolute error (IAE) by 0.25%, 0.37%, and 0.21%, respectively. Under sustained external loading, maximum-error reductions reached 9.33-10.20%, with mean actuator-wise peak-force changes within approximately ±2%. Additional simulations examined trajectory amplitude, synthetic measurement noise, viscous damping, and combined nonidealities. The results support FSPID as a conservative simulation-level refinement of fixed-gain PID; experimental validation remains necessary.
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