Model　predictive　control　(MPC)　provides　supports　for　controlling　the　NOx　emission　in　municipal　solid　waste　incineration　(MSWI)　process.　The　MSWI　process　suffers　from　dynamic　characteristic,　it　is　a　challenge　to　precisely　construct　a　prediction　model　online.　In　terms　of　this　problems,　an　R-SCN　based　MPC　method　is　proposed　in　this　work.　First,　the　nonlinear　prediction　model　of　NOx　emissions　is　established　offline　based　on　stochastic　configuration　network　(SCN).　Then,　the　output　weight　of　SCN　hidden　layer　is　updated　online　by　recursive　least　square　method.　Second,　the　particle　swarm　optimization　(PSO)　method　is　designed　for　calculating　the　optimal　control　law　of　each　control　sequence　in　the　constrained　receding-horizon　optimization.　Finally,　the　historical　data　of　a　waste　treatment　plant　is　used　to　validate　the　proposed　method.　And　the　experimental　results　show　that　the　dynamic　nonlinear　prediction　model　of　NOx　emissions　can　accurately　predict　the　variation　trend　of　NOx　value　and　the　proposed　control　method　can　realize　the　stable　control　of　NOx　concentration　in　MSWI　process.　©　2023　IEEE.