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Significant differences in measured performance and in perceived fidelity were evident across these configurations. The analytical model discussed in appendix B predicted a performance decrease when the motion filter natural frequency increased. However, the predicted bandwidths of the primary loop did not differ by a factor of 1.5, which was the general guideline suggested for determining dissimilarity between motion configuration responses (ref. 61). Although this analytical model is perhaps the most reasonable available, this experiment demonstrated that additional data are needed in order to continue its refinement and validation.
High Motion sensations are not noticeably different from those of visual flight
Medium Motion sensation differences are noticeable but not objectionable
Low Motion sensation differences are noticeable and objectionable
5. Vertical Experiment II: Compensatory Tracking
Background
In Vertical Experiment I, the global performance effects of motion-filter gain and natural frequency variations were examined during tracking. In Vertical Experiment II, a more detailed examination of the same filter variations was conducted for a new task: key pilot-vehicle frequency-response metrics were measured during combined tracking and disturbance regulation. This procedure allowed for the influence of the motion-filter changes to be examined simultaneously for these two important piloting tasks. The task and experimental apparatus are first described. Then, objective pilot-vehicle performance metrics and subjective motion-fidelity ratings are discussed.
Experimental Setup
Task
Figure 52 shows the display presented to the pilot. The object was to null the error between the moving target aircraft and the horizontal dashed line that was fixed to the pilot’s aircraft.
A system block diagram depicting how the error developed is shown in figure 53. Two external inputs were used in a scheme similar to that developed by Stapleford et al. (ref. 26).
e
Fixed horizontal line
δ
cd Aircraft
Figure 53. Vertical compensatory loop.
The target was driven by a sum-of-sines (SOS) input, and the vehicle was disturbed by a separate SOS input that was summed with the pilot’s collective position. These SOS’s were as follows:
ith( ) = . sin( . t) + 2 202 sin( .
2573 015 . 034 t)
. 064 0923 113 )
+ 1 563 sin( . t) + . sin( . t
(16)
. 205 0150 356 )
+
0 411 sin( . t) + . sin( . t
. sin(6 32 . t
+
0 040 ) feet
δcdt . sin(. t) + . sin( . t
() = 0029 028 0058 049 )
. 080 0167 150 )
+ 0 999 sin( . t) + . sin( . t
(17)
. 267 0201 463 )
+
0 209 sin( . t) + . sin( . t
. sin(8 50 . t
+
0 148 ) inches of collective
Each component of each SOS completed an integral number of cycles in the task time-length of 204.8 sec. A warm-up period of 10 sec preceded the run, and a cool-down period of 3 sec followed the run. To prevent the pilot from separating target motion from disturbance motion, the disturbance input, δ cd, was selected so that its resulting altitude spectral content (when filtered by the vehicle dynamics) matched the target shaping function (refs. 26, 41). If the pilot is able to separate the target motion (which is sensed only visually) from the distur-bance motion (which is sensed visually and vestibularly), previous research has shown that pilots may alter their behavior and potentially ignore the motion cues when nulling the target motion (ref. 26). The above spectral matching is an attempt to prevent this behavior.
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