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This paper proposes an identification technique of a human standing controller. The dynamics of a human is approximated by the macroscopic relationship between the center of mass and the zero-moment point. The standing controller is modelled by a piecewise-linear feedback, which was originally developed for humanoid robots. In the previous work, the authors found a qualitative similarity of the model to an actual human behavior observed in a phase space, and the next challenge was to identify the controller from those data. A difficulty is that the observed dynamics is a piecewise system due to the unilaterality of reaction forces, so that the identification is not straightforward. It is not trivial how to detect the switching point in each motion locus and how to find the trust region of the supposed model. The recursive-least-square (RLS) method, which can present the deviation of identified parameters and that of the reliability of the results, helps to estimate the trust region with a returning computation process. Through the identification, the validity of the proposed method was verified. More study about the availability of the COM-ZMP model and the piecewise-linear controller for the analyses of the human standing control is also reported.