Model　predictive　control　is　an　effective　way　to　achieve　the　control　of　wastewater　treatment　process　(WWTP).　However,　it　is　a　challenge　to　control　multiple　objectives　due　to　the　complexity　of　WWTP.　To　solve　this　problem,　an　eigenvector　based　multiobjective　model　predictive　control　(EMMPC)　strategy　is　developed　for　WWTP　to　handle　the　conflicting　objectives.　First,　a　multiobjective　control　scheme　is　designed　with　adaptive　fuzzy　neural　network　prediction　(AFNNP)　model　and　gradient　eigenvector　optimization　(GEO)　algorithm.　Then,　AFNNP　can　be　used　to　describe　the　nonlinear　of　WWTP　to　predict　the　controlled　variables.　Second,　GEO　is　presented　to　obtain　the　control　laws　of　the　multiple　control　objectives.　Specifically,　GEO　can　reduce　the　computational　burden　by　avoiding　the　determination　of　the　control　objective　weights.　Third,　the　stability　of　EMMPC　is　provided　in　theory.　Finally,　EMMPC　is　implemented　on　the　benchmark　simulation　platform　to　demonstrate　the　effectiveness　of　the　presented　multiobjective　control　method.　©　2023　IEEE.