A　Bi-stable　permanent　magnet　actuator　(BPMA)　shares　the　same　magnetic　circuit　as　the　breaking　and　closing　coils,　and　the　magnetic　flux　generated　by　any　coil　passes　through　the　breaking　and　closing　air　gaps.　The　permanent　magnet　automatically　distributes　the　permanent　magnetic　flux　according　to　the　dynamic　reluctance　of　the　air　gaps.　The　electromagnetic　flux　and　permanent　magnetic　flux　in　the　upper　and　lower　air　gaps　always　cause　the　moving　iron　core　to　be　coupled　by　two　opposite　magnetic　forces.　As　the　motion　of　the　moving　iron　core　and　the　change　of　coil　current,　the　magnetic　circuit　quickly　saturates,　and　the　electromagnetic　flux　and　permanent　magnetic　flux　interact,　exacerbating　the　complexity　of　nonlinear　coupling　in　the　breaking　and　closing　air　gaps.　To　flexibly　control　the　action　characteristics　of　permanent　magnet　switches,　it　is　necessary　to　simultaneously　control　the　air　gap　flux　and　the　magnetic　force　pointing　to　the　breaking　and　closing　positions.　Therefore,　this　paper　proposes　an　air　gap　flux　decoupling　control　method　based　on　finite　control　set-model　predictive　control　(FCS-MPC).　Decoupling　control　can　be　achieved　by　rapidly　weakening　the　magnetic　force　pointing　to　the　non-excited　coil　and　rapidly　increasing　the　magnetic　force　pointing　to　the　excited　coil.　Firstly,　according　to　the　operating　principle　of　BPMA,　the　vector　magnetic　force　acting　on　the　moving　iron　core　depends　on　the　＇magnetic　flux　squared　difference＇　of　the　breaking　and　closing　air　gaps.　Therefore,　only　controlling　this　vector　magnetic　flux　square　difference　in　real-time　can　dynamically　control　BPMA.　Secondly,　a　predictive　model　of　the　breaking　and　closing　air　gap　magnetic　flux　is　designed　through　discretization　of　the　voltage　balance　equation,　which　can　predict　the　magnetic　flux　at　the　next　moment　based　on　the　voltage　and　current　values　collected　at　the　current　moment.　Thirdly,　the　breaking　and　closing　air　gap　magnetic　flux　and　the　mechanism　drive　circuit　are　regarded　as　a　whole.　A　set　of　switching　states　is　constructed　through　the　excitation　intensity　analysis　under　different　switching　states.　Predictive　magnetic　flux　is　obtained　by　traversing　all　switching　state　combinations.　Finally,　a　decoupling　control　cost　function　is　designed,　the　predictive　magnetic　flux　under　different　switching　combinations　is　input　into　the　cost　function,　and　the　optimal　control　is　selected　for　the　next　control　period.　In　rolling　optimization　over　multiple　control　periods,　the　breaking　and　closing　air　gap　magnetic　flux　quickly　approaches　their　respective　reference　values,　achieving　decoupling　control.　A　co-simulation　platform　for　intelligent　control　is　designed　based　on　LabVIEW　and　Multisim,　and　hardware　testing　circuits　are　constructed.　The　simulation　and　experimental　waveforms　show　that　this　proposed　scheme　can　effectively　control　the　breaking　and　closing　air　gap　flux.　As　a　result,　the　non-excited　air　gap　flux　to　zero　is　quickly　reduced,　approaching　the　set　reference　value　of　the　excited　air　gap　flux　and　effectively　weakening　the　coupling　between　the　air　gaps.　Compared　with　the　traditional　current　closed-loop　control　scheme,　the　proposed　control　scheme　reduces　the　energy　loss　during　the　entire　action　process　and　improves　the　response　and　action　time　of　the　core　action.　©　2025　China　Machine　Press.　All　rights　reserved.