Blind decorrelation is a related task to blind source separation (BSS) which is applicable to numerous problems. A critical challenge in adaptive blind decorrelation (ABD) is the choice of step size to achieve fast initial convergence speed and low steady state error in time-varying systems. Unfortunately, unlike some supervised training, the error factor of ABD is inaccessible in practice, and so the relation between step size and error factor can not be utilized to adjust the step size. In this paper, we first present an algorithm to restructure the error factor by adopting an auxiliary decorrelation system with some restriction, and then based on a nonlinear updating rule of step-size in the light of the error factor descending in an exponential form, we propose a novel variable step size algorithm for ABD. Simulation results indicate the good performance of our proposed method.