Model reference adaptive control (MRAC) can effectively handle various challenges of the real world control problems including exogenous disturbances, system uncertainties, and degraded modes of operations. In human-in-the-loop settings, MRAC may cause unstable system trajectories. Basing on our recent work on the stability of MRAC-human dynamics, here we follow an optimization based computations to design a linear filter and study whether or not this filter inserted between the human model and MRAC could help remove such instabilities, and potentially improve performance. To this end, we present a mathematical approach to study how the error dynamics of MRAC could favorably or detrimentally influence human operator's error dynamics in performing a certain task. An illustrative numerical example concludes the study.