This　article　is　concerned　with　the　stabilization　problem　of　nonlinear　networked　control　systems　(NCSs)　subject　to　successive　packet　losses　(SPLs),　probabilistic　sampling　(PS),　and　input　dynamic　quantization.　Specifically,　the　Takagi-Sugeno　(T-S)　fuzzy　system　is　used　to　approximate　the　nonlinear　plant,　and　the　model　of　SPLs　is　used　to　describe　packet　losses　occurring　in　the　sensor-to-controller　and　controller-to-actuator　channels,　while　PS　is　represented　by　a　Bernoulli　distribution.　First,　by　considering　the　double　randomness　of　both　the　SPL　model　and　PS,　a　unified　model　is　proposed　to　evaluate　the　probability　of　the　sampling　interval　between　two　successive　update　times.　Second,　by　introducing　probability　knowledge　and　using　the　exact-time　discrete　approach,　the　stochastic　stability　condition　is　established　for　the　constructed　equivalent　discrete-time　T-S　fuzzy　system　in　the　presence　of　input　dynamic　quantization.　Third,　based　on　the　established　stability　condition,　the　fuzzy　controller　is　designed.　Finally,　the　networked　mass-spring　mechanical　system　is　given　to　show　the　validity　of　the　proposed　approach,　and　the　merits　of　the　proposed　design　approach　are　discussed　in　comparison　to　existing　results.