This　article　is　dedicated　to　studying　realization　issues　of　the　stability　performance-based　nonlinear　fault-tolerant　control　framework　via　Takagi-Sugeno　(T-S)fuzzy　models.　To　this　end,　the　nonlinear　fault-tolerant　control　strategy　with　an　online　fault　detection　system　monitoring　the　system　stability　performance　degradation　induced　by　faults　is　first　introduced　by　means　of　the　stable　image　and　kernel　representations.　On　this　basis,　the　T-S　fuzzy　models　are　applied　to　approximate　the　nonlinear　system,　and　a　design　approach　of　the　fuzzy　observer-based　controller　is　proposed　for　the　system　stabilization　via　the　iterative　linear　matrix　inequality　method.　With　the　controller　gains,　the　fuzzy-model-based　nominal　stable　image　representation　of　the　system　is　formulated,　which　leads　to　the　generation　of　the　input　and　output　error　signals.　Then,　with　the　reference　signal　and　system　input　and　output　error　signal　data,　a　data-driven　algorithm　is　given　to　online　estimate　the　evaluation　function　defined　in　terms　of　system　uncertainties　and　faults.　By　virtue　of　the　L-2　input-output　stability　of　the　controller　stable　kernel　representation,　a　threshold　calculation　method　is　presented　and,　thus,　the　stability　performance-based　fault　detection　system　based　on　fuzzy　models　is　realized.　Furthermore,　for　fault-tolerant　purpose,　the　fault-tolerant　controller　design　is　discussed,　which　aims　to　retain　the　system　stability.　Two　examples　are　provided　in　the　end　to　illustrate　the　proposed　results.