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This paper presents an H-infinity filtering approach to optimize a fuzzy control model used to determine behavior-consistent (BC) information-based control strategies to improve the performance of congested dynamic traffic networks. By adjusting the associated membership function parameters to better respond to nonlinearities and modeling errors, the approach is able to enhance the computational performance of the fuzzy control model. Computational efficiency is an important aspect in this problem context, because the information strategies are required in subreal time to be real-time deployable. Experiments are performed to evaluate the effectiveness of the approach. The results indicate that the optimized fuzzy control model contributes in determining the BC information-based control strategies in significantly less computational time than when the default controller is used. Hence, the proposed H-infinity approach contributes to the development of an efficient and robust information-based control approach.