To interpret the nonlinear system identification of multi-degree-of-freedom vibrating structures with freeplay, an estimation procedure based on subspace method in time domain is developed in this paper. Two types of freeplay, namely, central freeplay and offset freeplay, are estimated. Besides, the frequency response function matrices of the underlying linear system and overlying linear system are identified. By considering an all movable fin from a portion of a supersonic flutter test platform containing freeplay on the rigid rotating motion, two series of numerical experiments are applied for demonstration. Results show that the proposed approach indicates a high and reliable recognition of freeplay regions and the nominal linear system. The limitations of the method in this study are also discussed.With the development of system identification and control theory, nonlinear black-box modeling, like the Hammerstein-Wiener model, was proposed and widely used in control of the nonlinear system. A variety of identification methods were developed to estimate the nonlinear and linear model [18][19][20][21][22]. However, the establishment of the black-box model is based on data alone, lacking physical insight. This is a very ambitious objective knowing that nonlinearity may be caused by many different mechanisms and may result in a plethora of dynamic phenomena [1].Recently, two types of feedback formulation on nonlinear system identification were developed, namely, reverse path (RP) method and nonlinear identification through feedback of the output (NIFO) method. Bendat [23] first introduced the RP method to a single-degree-of-freedom (SDOF) system and by Rice [24] to a multi-degree-of-freedom (MDOF) system. However, the requirement of exciting all the measured DOF was the obstacle to extensive applications for the RP method. Then, Richards and Singh [25] proposed the conditioned reverse path (CRP) method to overcome this limitation, but with more complicated RP formulation and more substantial computational burden.Another type of feedback formulation is the NIFO method put forward by Adams and Allemang [26], who introduced a least-squares parameter estimation method to decouple the linear and nonlinear parameters during the nonlinear identification of a multi-input, multi-output (MIMO) system. Then, the subspace-based identification methods were introduced to the identification of nonlinear mechanical systems by taking advantage of this kind of nonlinear feedback interpretation. Marchesiello and Garibaldi [27] proposed the time-domain nonlinear subspace identification (TNSI) method firstly and Noël and Kerschen [28] developed the counterpart frequency-domain nonlinear subspace identification (FNSI) method. Then, a comparison between the capabilities of TNSI and FNSI was addressed by Noël [29] considering a series of numerical experiments towards a nonlinear SmallSat spacecraft along with stochastic analysis.Smooth structural nonlinearities were chosen as demonstrations of system identification methods. However, th...