To　enhance　the　safety　of　direct　physical　interaction　between　humans　and　lower-limb　exoskeletons,　the　actuator　of　the　lower-limb　exoskeleton　should　possess　compliance,　force　controllability,　and　back-drivability.　In　this　paper,　a　novel　compact　compliant　force　control　actuator　with　worm　gear　and　gear　rack　as　transmission　modes　is　designed　to　provide　flexible　power　to　the　lower-limb　exoskeleton.　The　worm　gear　is　utilized　to　amplify　the　torque　generated　by　the　motor　in　the　compact　compliant　actuator,　while　the　gear　rack　is　established　to　improve　the　bearing　capacity.　Yet,　the　friction　is　occurred　between　the　worm　gear,　rack　and　other　mechanical　configurations　which　may　lead　to　non-negligible　force　control　error　of　the　compliant　actuator.　A　noise-tolerant　zeroing　neural　network　controller　is　proposed　to　suppress　noises.　Additionally,　theoretical　proofs　are　provided　for　the　convergence　performance　of　the　noise-tolerant　zeroing　neural　network　controller,　as　well　as　the　suppression　of　constant　noise,　linear　disturbances,　and　bounded　random　noise.　The　proposed　noise-tolerant　zeroing　neural　network　controller　is　validated　on　the　compliant　actuator　through　numerical　simulations,　experimental　results,　and　comparison　experiments,　demonstrating　its　effectiveness　in　suppressing　various　noise　and　improving　the　convergence,　stability,　and　robustness　of　the　compliant　actuator　system.　Additionally,　the　controller　is　further　verified　through　walking　experiments　conducted　on　a　knee　robot.　©　The　Author(s),　under　exclusive　licence　to　Springer-Verlag　London　Ltd.,　part　of　Springer　Nature　2024.