Current motion-drive algorithms have a number of coefficients that are selected to tune the motion of the simulator. Little attention has been given to the process of selecting the most appropriate coefficient values. Final tuning is best accomplished using experienced evaluation pilots to provide feedback to a washout filter expert who adjusts the coefficients in an attempt to satisfy the pilot. This paper presents the development of a tuning paradigm and the capturing of such within an expert system. The focus of this development is the University of Toronto classical algorithm, but the results are relevant to alternative classical and similarly structured adaptive algorithms. This paper provides the groundwork required to develop the tuning paradigm. The necessity of this subjective tuning process is defended. Motion cueing error sources within the classical algorithm are revealed, and coefficient adjustments that reduce the errors are presented.