The　unique　stator　structure　of　bearingless　flux-switching　permanent　magnet　motors　(BFSPMM)　generates　the　suspension　force　of　the　rotor　influenced　by　the　coupling　effects　of　self-inductance　of　the　suspension　winding,　mutual　inductance　between　the　suspension　winding　and　the　torque　winding,　and　rotor　angle.　However,　previous　suspension　force　modeling　schemes　have　not　fully　considered　the　influence　of　the　coupled　electromagnetic　force,　resulting　in　low　accuracy　of　the　suspension　force　model.　The　inverse　system　decoupling　control　method　relies　on　a　high-precision　mathematical　model.　Therefore,　establishing　a　more　accurate　suspension　force　model　is　the　key　to　achieving　high-performance　decoupling　control　of　the　motor　suspension.　This　paper　proposes　an　inverse　system　control　strategy　based　on　least　squares　support　vector　machine　(LSSVM).　The　model　accuracy　is　improved　to　fit　and　compensate　for　the　coupled　electromagnetic　force,　and　the　performance　of　the　suspension　inverse　system　control　is　enhanced.　Based　on　the　rotor　motion　equation,　the　coupling　effect　of　the　gyroscopic　effect　force　and　the　coupled　electromagnetic　force　in　the　suspension　force　on　the　rotor　radial　displacement　of　BFSPMM　is　analyzed.　Random　current　excitations　within　a　limited　range　are　applied　to　the　finite　element　model　of　BFSPMM　to　obtain　the　operating　data　set　under　different　rotor　position　angles　and　radial　displacements.　The　operating　data　set　trains　LSSVM　to　obtain　the　LSSVM　prediction　model　of　the　coupled　electromagnetic　force.　During　the　motor　operation,　the　operating　data　is　sent　to　the　LSSVM　prediction　model　to　obtain　the　real-time　predicted　value　of　the　coupled　electromagnetic　force.　It　is　compensated　to　the　original　system　through　the　force-current　relationship　to　decouple　initially.　Finally,　the　inverse　system　method　decouples　the　nonlinearity　of　the　gyroscopic　effect　coupling　part　of　the　suspension　system,　achieving　complete　decoupling　of　the　BFSPMM　rotor　suspension　system.　The　simulation　results　show　that　the　predicted　value　of　the　coupled　electromagnetic　force　by　LSSVM　is　close　to　that　of　the　finite　element　simulation,　with　high　prediction　accuracy.　Suppose　the　rated　operating　condition　of　the　motor　with　a　speed　of　1　500　r/min　and　a　torque　of　4　N·m.　The　results　show　that　during　the　start-up　of　suspension,　the　rotor　radial　displacement　overshoot　of　the　proposed　control　strategy　is　smaller　and　the　system　stability　is　better　than　that　of　the　PID　control.　Similarly,　when　a　sudden　change　occurs　in　the　suspended　load,　the　rotor　under　the　PID　control　strategy　generates　a　large　amplitude　fluctuation　in　the　radial　displacement,　with　a　maximum　value　of　0.023　mm.　In　contrast,　the　rotor　displacement　of　the　proposed　control　strategy　is　almost　unaffected.　The　experimental　results　show　that　the　radial　displacement　of　the　proposed　control　strategy　under　the　rated　condition　is　controlled　within　0.054　mm,　only　45.0%　of　that　of　the　PID　control.　Under　different　speed　and　torque　conditions,　the　rotor　radial　displacement　can　also　be　controlled　within　0.076　mm.　Additionally,　when　a　sudden　disturbance　is　applied　to　the　x-axis,　the　radial　displacement　in　the　x-axis　direction　generates　a　disturbance　of　0.15　mm,　while　the　y-axis　is　almost　unaffected.　Likewise,　when　a　sudden　disturbance　is　applied　to　the　y-axis,　the　radial　displacement　in　the　y-axis　direction　generates　a　disturbance　of　0.13　mm,　while　the　x-axis　is　almost　unaffected.　The　proposed　control　strategy　achieves　decoupling　control　of　the　suspension　system.　The　conclusions　are　as　follows.　(1)　LSSVM　can　approximate　the　coupled　electromagnetic　force　in　the　suspension　force,　improve　the　accuracy　of　the　model,　and　enhance　the　decoupling　control　effect　of　the　suspension　inverse　system.　(2)　The　proposed　control　strategy　significantly　improves　the　rotor　radial　displacement　ripple　and　has　good　dynamic　decoupling　performance.　©　2025　China　Machine　Press.　All　rights　reserved.