A　continuous　control　set　model　predictive　speed　control　(CCS-MPSC)　strategy　based　on　the　particle　swarm　optimization　(PSO)　algorithm　is　proposed,　where　the　cost　function　of　model　predictive　speed　control　(MPSC)　is　regarded　as　the　objective　function　to　evaluate　the　fitness　of　the　particles.　During　this　process,　all　particles　are　ordered　to　conduct　optimization　under　the　hexagonal　sector　composed　of　voltage　space　vectors.　At　the　end,　the　particles　coverage　to　the　optimal　value　through　keeping　updating　particle　positions.　As　the　feedback,　the　system　obtains　the　optimal　voltage　vector　without　the　derivation　of　error　model　and　realizes　CCS-MPSC.　According　to　the　simulation　results,　the　effectiveness,　and　the　robustness　of　speed　control　with　mutative　work　conditions.　©　2021　IEEE.