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This paper proposes an accurate and cost-effective COG defuzzifier of fuzzy logic controller (FLC). The accuracy of the proposed COG defuzzifier is obtained by involving both membership values and spans of membership functions in calculating a crisp value. The cost-effectiveness of the proposed COG defuzzifier is obtained by finding the moment equilibrium point instead of computing the division in the COG defuzzifier. The proposed COG defuzzifier has two disadvantages: it increases the hardware complexity due to the additional multipliers and it takes a lot of computation time to find the moment equilibrium point. The first disadvantage is overcome by replacing the multipliers with the stochastic AND operations. The second disadvantage is alleviated by using a coarse-to-fine searching algorithm that accelerates the finding of moment equilibrium point by O(M) maximally when compared with the equal interval searching method of Ruiz et al. (1995). Application of the proposed COG defuzzifier to the truck backer-upper control problem is performed in the VHDL simulation and the control accuracy of the proposed COG defuzzifier is compared with that of the conventionally simplified COG defuzzifier in terms of average tracing distance.