With　the　advancement　of　science　and　technology,　more　and　more　complex　systems　require　the　model　to　have　the　ability　to　output　multiple　parameters　simultaneously.　Fuzzy　neural　network　(FNN)　is　widely　used　in　complex　system　modeling　because　of　its　combination　of　the　nonlinear　analysis　ability　of　artificial　neural　network　(ANN)　and　the　fuzzy　inference　ability　of　fuzzy　system.　Therefore,　this　paper　constructs　a　multi-input　and　multi-output　(MIMO)　model　based　on　T-S　(Takagi-Sugeno)　FNN.　First,　according　to　the　construction　mechanism　of　TS-FNN,　the　MIMO　network　structure　is　designed.　Then,　a　multi-output　parameter　update　algorithm　is　designed,　which　takes　into　account　the　global　performance　and　local　performance　of　the　network.　Finally,　simulation　experiments　are　designed　through　benchmark　experiments　and　modeling　problems　in　an　industrial　process,　which　proves　the　feasibility　and　effectiveness　of　the　neural　network　model.　©　2021　IEEE.