Wastewater　treatment　plays　a　crucial　role　in　alleviating　water　shortages　and　protecting　the　environment　from　pollution.　Due　to　the　strong　time　variabilities　and　complex　nonlinearities　within　wastewater　treatment　systems,　devising　an　efficient　optimal　controller　to　reduce　energy　consumption　while　ensuring　effluent　quality　is　still　a　bottleneck　that　needs　to　be　addressed.　In　this　paper,　in　order　to　comprehensively　consider　different　needs　of　the　wastewater　treatment　process　(WTTP),　a　two-objective　model　is　to　consider　a　scope,　in　which　minimizing　energy　consumption　and　guaranteeing　effluent　quality　are　both　considered　to　improve　wastewater　treatment　efficiency　To　efficiently　solve　the　model　functions,　a　grid-based　dynamic　multi-objective　evolutionary　decomposition　algorithm,　namely　GD-MOEA/D,　is　designed.　A　GD-MOEA/D-based　intelligent　optimal　controller　(GD-MOEA/D-IOC)　is　devised　to　achieve　tracking　control　of　the　main　operating　variables　of　the　WTTP.　Finally,　the　benchmark　simulation　model　No.　1　(BSM1)　is　applied　to　verify　the　validity　of　the　proposed　approach.　The　experimental　results　demonstrate　that　the　constructed　models　can　catch　the　dynamics　of　WWTP　accurately.　Moreover,　GD-MOEA/D　has　better　optimization　ability　in　solving　the　designed　models.　GD-MOEA/D-IOC　can　achieve　a　significant　improvement　in　terms　of　reducing　energy　consumption　and　improving　effluent　quality.　Therefore,　the　designed　multi-objective　intelligent　optimal　control　method　for　WWTP　has　great　potential　to　be　applied　to　practical　engineering　since　it　can　easily　achieve　a　highly　intelligent　control　in　WTTP.