Fast　and　precise　control　of　velocity　is　one　of　the　key　factors　for　the　vehicles　to　obtain　good　control　quality　in　their　movement.　The　paper　introduces　fractional　order　PIλDµ　(FOPID)　controller　into　velocity　control　of　micro　intelligent　vehicles　(MicroIVs).　Because　the　selection　of　parameters　for　FOPID　controller　with　two　additional　parameters　λ　and　µ　is　more　difficult　than　traditional　integer　order　PID　(IOPID)　controller,　an　improved　back　propagation　(BP)　neural　network　is　proposed　and　used　in　the　parameters　tuning　of　FOPID　controllers.　The　implementation　of　FOPID　controller　is　also　difficult　because　fractional　calculus　operators　of　FOPID　controller　cannot　be　directly　implemented　in　numerical　calculation.　Fractional　order　calculus　is　transformed　from　continuous　time　domain　to　discrete　time　domain　by　using　the　Al-Alaoui　generating　function,　and　is　discretized　by　using　the　continued　fraction　expansion　(CFE).　FOPID　controller　is　implemented　in　motor　velocity　control　for　MicroIVs,　and　the　robustness　and　rapidity　of　FOPID　controller　are　verified　by　the　methods　of　this　paper.　The　results　of　experiment　show　that　FOPID　controller　has　better　control　performance　than　IOPID　controller.　©　2018,　ICIC　Express　Letters　Office.　All　rights　reserved.