For　the　uncertain　nonlinear　systems,　the　disturbance　caused　by　external　factors　can　affect　the　accuracy　of　tracking　control.　To　solve　this　issue,　a　hierarchical　self-organizing　fuzzy　control　(HSOFC)　strategy　is　proposed　to　improve　the　tracking　control　performance.　First,　the　self-organizing　fuzzy　neural　network　is　employed　as　a　fuzzy　approximator　to　estimate　the　unknown　nonlinear　function.　Specifically,　a　hierarchical　strategy　is　designed　to　improve　the　estimation　accuracy　by　preventing　the　wrong　pruning　of　rules,　without　setting　the　pruning　threshold　based　on　rule　density　and　significance.　Second,　an　additional　robust　control　component　based　on　sliding　mode　surface　is　designed　to　suppress　the　influence　on　the　control　performance　by　external　disturbances　and　the　approximation　error.　Furthermore,　to　further　improve　the　robust　control　performance　and　reduce　computational　complexity,　an　adaptive　allocation　strategy　is　studied　to　set　the　parameters　of　HSOFC.　Finally,　the　stability　of　HSOFC　is　proven.　The　simulation　results　show　that　HSOFC　can　reduce　computational　complexity　and　obtain　accurate　tracking　control　performance.