Adaptive　dynamic　programming　(ADP)　has　been　tested　as　an　effective　method　for　optimal　control　of　nonlinear　system.　However,　as　the　structure　of　ADP　requires　control　input　to　satisfy　the　initial　admissible　control　condition,　the　control　performance　may　be　deteriorated　due　to　abrupt　parameter　change　or　system　failure.　In　this　paper,　we　introduce　the　multiple　models　idea　into　ADP,　multiple　subcontrollers　run　in　parallel　to　supply　multiple　initial　conditions　for　different　environments,　and　a　switching　index　is　set　up　to　decide　the　appropriate　initial　conditions　for　current　system.　By　taking　this　strategy,　the　proposed　multiple　model　ADP　achieves　optimal　control　for　system　with　jumping　parameters.　The　convergence　of　multiple　model　adaptive　control　based　on　ADP　is　proved　and　the　simulation　shows　that　the　proposed　method　can　improve　the　transient　response　of　system　effectively.