In　this　paper,　an　optimal　trajectory　tracking　control　problem　for　general　nonlinear　systems　is　investigated.　An　adaptive　critic　control　method　with　the　digital　twin　(DT)　theory　is　developed.　Divergent　from　the　existing　tracking　control　methods,　the　advantages　of　adaptive　dynamic　programming　(ADP)　and　the　theory　of　DT　are　combined　in　this　paper,　and　the　novel　multilayer　artificial　system　structure　is　constructed.　The　actioncritic　structure　is　employed　by　each　artificial　system　to　obtain　an　approximate　optimal　control　policy.　The　model　network　(MN)　is　built　by　using　the　actual　input　and　output　data　sets　of　the　controlled　system,　which　means　the　dependence　on　the　dynamics　of　the　system　is　overcame.　Then,　the　weights　of　the　trained　action　network　(AN)　and　MN　are　passed　to　the　real　system　to　realize　the　optimal　tracking　control.　The　feasibility　of　the　algorithm　is　proved　by　theoretical　analysis.　Finally,　the　algorithm　is　applied　to　a　simple　nonlinear　torsional　pendulum　system　and　an　industrial　wastewater　treatment　system　(WWTS),　and　the　effectiveness　of　the　algorithm　is　verified.　The　algorithm　effectively　realizes　the　tracking　control　of　nonlinear　systems.