Extractive　dividing　wall　column　(EDWC)　is　a　typical　process　intensification　technology　and　possesses　significant　energy-saving　prospects,　while　the　poor　dynamic　controllability　hinders　its　industrialization　goal.　In　this　work,　taking　the　benzene　and　cyclohexene　azeotrope　separation　as　an　example,　a　proportional-integral　(PI)　control　structure　based　on　four-point　temperature　control　loops　is　proposed　for　EDWC　by　considering　temperature　difference　as　the　discriminant　criterion.　Subsequently,　to　improve　the　control　performance　of　EDWC,　two　model　predictive　control　(MPC)　structures　based　on　auto-regressive　with　external　input　(ARX)　model　obtained　from　closed-loop　identification　and　linear　time-invariant　state-space　(LTI-SS)　model,　respectively,　are　studied　for　EDWC.　The　performance　of　three　control　structures　is　tested　by　+/-　20　%　feed　flow　rate　and　composition　disturbances,　and　further　quantitatively　evaluated　by　integral　absolute　error　(IAE).　The　dynamic　responses　demonstrate　that　the　ARX-based　MPC　structure　achieves　the　best　control　performance　in　the　presence　of　feed　flow　rate　and　composition　disturbances,　which　can　be　attributed　to　the　capability　of　the　identified　ARX　model　to　track　the　dynamic　features　of　EDWC　accurately.