Current motion-drive algorithms have a number of coefficients that are
selected to tune the motion of the simulator, Little attention has be
en 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 T
oronto classical algorithm, but the results are relevant to alternativ
e classical and similarly structured adaptive algorithms, This paper p
rovides the groundwork required to develop the tuning paradigm. The ne
cessity of this subjective tuning process is defended, Motion cueing e
rror sources within the classical algorithm are revealed, and coeffici
ent adjustments that reduce the errors are presented.