© 2022, American Institute of Aeronautics and Astronautics Inc. All rights reserved.In this study, we propose a new adaptive weight update law using frequency-limited estimation of the matched uncertainty. Many adaptive parameter adjustment laws try to suppress the effects of uncertainties using forcing terms consisting of tracking error only. However, it has been widely studied that including the uncertainty estimation error in the adaptation law enhances the transient performance significantly. In our proposed solution, low-frequency estimation of the uncertainty is included in the adaptation in a time-varying learning rate structure. Also, with the proposed architecture, an explicit bound on the convergence rate of frequency-limited uncertainty estimation error is presented. Unlike the other filter-based methods, the proposed modification term compensates the information lost when the signal is filtered to suppress the high-frequency content. Furthermore, the proposed solution introduces a regulation term to the standard adaptive weight update law which behaves like a stability augmentation in the adaptive system. The closed-loop stability of the proposed solution is illustrated through Lyapunov’s stability theorem. Morevover, efficacy of the proposed solution is revealed by the numerical simulations.