In　the　municipal　solid　waste　incineration　process,　it　is　difficult　to　effectively　control　the　gas　oxygen　content　by　setting　the　air　flow　according　to　artificial　experience.　To　address　this　problem,　this　paper　proposes　an　optimization　control　method　of　gas　oxygen　content　based　on　model　predictive　control.　First,　a　stochastic　configuration　network　is　utilized　to　establish　a　prediction　model　of　gas　oxygen　content.　Second,　an　improved　differential　evolution　algorithm　that　is　based　on　parameter　adaptive　and　t‐distribution　strategy　is　employed　to　address　the　set　value　of　air　flow.　Finally,　model　predictive　control　is　combined　with　the　event　triggering　strategy　to　reduce　the　amount　of　computation　and　the　controller’s　frequent　actions.　The　experimental　results　show　that　the　optimization　control　method　proposed　in　this　paper　obtains　a　smaller　degree　of　fluctuation　in　the　air　flow　set　value,　which　can　ensure　the　tracking　control　performance　of　the　gas　oxygen　content　while　reducing　the　amount　of　calculation.　©　2024　by　the　authors.