In　this　paper,　the　incremental　harmonic　balance　nonlinear　identification　(IHBNID)　is　presented　for　modelling　and　parametric　identification　of　nonlinear　systems.　The　effects　of　harmonic　balance　nonlinear　identification　(HBNID)　and　IHBNID　are　also　studied　and　compared　by　using　numerical　simulation.　The　effectiveness　of　the　IHBNID　is　verified　through　the　Mathieu-Duffing　equation　as　an　example.　With　the　aid　of　the　new　method,　the　derivation　procedure　of　the　incremental　harmonic　balance　method　is　simplified.　The　system　responses　can　be　represented　by　the　Fourier　series　expansion　in　complex　form.　By　keeping　several　lower-order　primary　harmonic　coefficients　to　be　constant,　some　of　the　higher-order　harmonic　coefficients　can　be　self-adaptive　in　accordance　with　the　residual　errors.　The　results　show　that　the　IHBNID　is　highly　efficient　for　computation,　and　excels　the　HBNID　in　terms　of　computation　accuracy　and　noise　resistance.