Municipal　wastewater　treatment　process　(MWWTP)　is　a　typical　complex　industrial　process,　where　multiple　dynamic　performance　indices　are　contained　in　the　optimal　operational　process.　To　realize　the　optimal　operational　control　of　MWWTP,　a　dynamic　multiobjective　intelligent　optimal　control　(DMIOC)　strategy　is　proposed　in　this　paper.　First,　dynamic　performance　index　model　based　on　adaptive　kernel　function　was　established.　Then　the　dynamic　characteristics　of　performance　indices　could　be　accurately　captured.　Second,　a　dynamic　multiobjective　particle　swarm　optimization　(DMOPSO)　algorithm,　based　on　an　adaptive　flight　parameter　adjustment　mechanism,　was　designed.　It　can　efficiently　balance　the　diversity　and　convergence　of　the　particles.　Then　the　real-time　optimal　setpoints　of　the　control　variables　dissolved　oxygen　and　nitrate　nitrogen　could　be　obtained.　Third,　a　multi-loop　PID　control　strategy　was　utilized　to　realize　the　control　of　the　optimal　set-points　of　dissolved　oxygen　and　nitrate　nitrogen.　The　proposed　DMIOC　strategy　was　tested　in　the　benchmark　simulation　model　to　evaluate　its　effectiveness.　The　results　demonstrate　that　the　proposed　DMIOC　strategy　can　realize　the　dynamic　optimal　control　of　the　control　variables　dissolved　oxygen　and　nitrate　nitrogen,　guarantee　the　effluent　qualities　in　the　limits　and　reduce　the　operation　cost.　Copyright　©　2021　Acta　Automatica　Sinica.　All　rights　reserved.