In　order　to　improve　road　traffic　safety　and　efficiency,　this　paper　studies　the　modeling　and　control　problem　of　the　mixed　vehicle　platoon　consisting　of　connected　autonomous　vehicles　(CAVs)　and　human-driven　vehicles　(HDVs).　Firstly,　a　data-driven　linear　model　of　the　mixed　vehicle　platoon　is　constructed　by　the　Extended　Dynamic　Mode　Decomposition　(EDMD)　algorithm　to　approximate　the　infinite-dimensional　Koopman　operator.　Different　from　the　existing　related　work,　we　consider　model　mismatch　errors　in　the　data-driven　linear　model.　Secondly,　a　tube　model　predictive　controller　is　designed　for　the　mixed　vehicle　platoon　so　that　the　actual　state　trajectories　of　all　vehicles　in　the　platoon　are　constrained　in　a　tube　centering　on　the　nominal　trajectory,　which　converges　to　the　desired　state.　Finally,　it　is　verified　by　numerical　simulation　that　the　proposed　data-driven　modeling　method　can　accurately　model　the　system,　and　the　designed　tube　MPC　controller　can　overcome　the　negative　effects　of　model　mismatch　errors　to　achieve　the　platoon　control　objective.　©　2023　Technical　Committee　on　Control　Theory,　Chinese　Association　of　Automation.