The　increasing　complexity　and　scale　of　the　wastewater　treatment　process　(WWTP)　demand　more　and　more　safety　and　stability.　However,　due　to　the　unavoidable　existence　of　external　disturbance,　sludge　bulking　is　commonly　encountered,　which　can　result　in　risks　for　the　efficient　and　stable　operation　of　WWTP.　To　address　this　problem,　a　knowledge-data-driven　robust　fault-tolerant　control　(KDD-RFTC)　is　proposed　in　this　article.　First,　a　robustness　evaluation　strategy　(RES)　is　constructed　to　extract　the　response　and　fluctuation　characteristics　of　KDD-RFTC.　Then,　the　antijamming　ability　of　KDD-RFTC　can　be　obtained　in　the　presence　of　sludge　bulking.　Second,　an　adaptive　knowledge　transfer　strategy　(AKTS),　based　on　RFTC,　is　designed　to　suppress　the　sludge　bulking　with　the　knowledge　from　the　results　of　RES　and　the　process　data.　Then,　the　proposed　KDD-RFTC　can　readjust　the　manipulated　variable　to　ensure　a　safe　and　stable　operation.　Third,　the　stability　proof　of　KDD-RFTC　is　verified　by　the　Lyapunov　theory.　Then,　the　successful　application　of　KDD-RFTC　can　be　guaranteed.　Finally,　KDD-RFTC　is　employed　in　the　benchmark　simulation　model　no.　1　(BSM1)　to　verify　its　merits.　The　experimental　results　illustrate　that　the　proposed　KDD-RFTC　method　can　obtain　excellent　control　performance　and　inhibit　sludge　bulking.