The　wastewater　treatment　process　(WWTP),　including　multiple　operation　conditions,　is　a　complex　industrial　process　with　strong　nonlinearity　and　time-varying　dynamics.　It　is　a　challenge　to　design　an　effective　controller　for　this　kind　of　process.　To　solve　this　problem,　a　knowledge-data-driven　flexible　switching　controller　is　designed　and　analyzed　to　achieve　reliable　control　performance.　First,　a　flexible　switching　control　strategy　is　proposed　to　build　multiple　operation　models　to　approximate　different　operation　conditions.　Then,　multiple　subcontrollers　are　designed　for　the　multiple　operation　models　to　suppress　the　nonlinearity　and　time-varying　dynamics　of　WWTP.　Second,　a　knowledge-data-driven　framework,　based　on　data　sharing　and　knowledge-driven　mechanisms,　is　developed　to　learn　the　subcontrollers.　Then,　the　internal　data　and　external　knowledge　can　be　fully　leveraged　to　improve　the　control　accuracy.　Third,　the　stability　of　the　proposed　control　strategy　is　given　in　detail.　The　corresponding　stability　conditions　are　provided　to　guide　its　application.　Finally,　the　control　performance　is　confirmed　on　the　benchmark　simulation　model　No.　1.　The　results　demonstrate　that　the　proposed　KDFSC　can　achieve　excellent　control　performance.