In traditional power system state estimation (PS-SE), the iterative step size of the state correction equation is generally fixed. But this method often fails to converge effectively because of the low data quality and complex network conditions. For the purpose of solving this problem and improving the suitability of state estimation, the classical logic function is reconstructed to find the generating function which is naturally suitable for the high-quality numerical iteration of state estimation on the image. Then, this function is considered as the step size control factor, and the step size factor can be adjusted intelligently by controlling parameters. After that, the weight factor function introdueced to make the algorithm perform variable weight operation in the iterative process and the influence from the bad data can be reduced then. Compared with the analytical method in terms of an adjustable step size, this method has the characteristics of low coupling in model and strong portability. Consider an IEEE30 node system as example. It is found that the proposed algorithm is superior to the traditional fixed step size method in terms of numerical stability, computation efficiency, and estimated quality when the measurement has bad data and the power system is under quasi ill-conditioned and ill-conditioned.