**6. Conclusions**

16 Will-be-set-by-IN-TECH

Node Max. Freq. Min. Freq. Real Freq. Consume 70 280 40 0.002 50 260 250 0.002 50 250 100 0.002 55 300 50 0.002

<sup>0</sup> 0.02 0.04 0.06 0.08 0.1 <sup>0</sup>

**Figure 9.** Frequencies bounded into a schedulability region usign a frequency transmission controller

rate. In second 9 fault appears with a change of context, system transmits with this frequency until second 18. In second 19 frequency transition model change frequencies of backup tasks.

Pitch signal

<sup>0</sup> <sup>5</sup> <sup>10</sup> <sup>15</sup> <sup>20</sup> <sup>25</sup> <sup>30</sup> -50

<sup>0</sup> <sup>5</sup> <sup>10</sup> <sup>15</sup> <sup>20</sup> <sup>25</sup> <sup>30</sup> -20

**Figure 10.** Pitch and yaw signals in a fault scenario using frequency transmission model

Time

Time

Yaw signal

Time(secs)

node1 node2 node3 node4

**Table 1.** Maximum, minimum, and real frequencies besides the computational time

50

0

Degree

Degree

50

100

150

Frequency

200

250

This work show a study of network scheduling strategy using numerical simulations. A simulation of a particular RTDS, a 2-DOF helicopter, is built using TrueTime as real-time simulation tool. A network scheduling strategy based on changes of frequency transmission rates is implemented in order to expose the advantages of using dynamic scheduling in an ad-hoc implementation for the network of a NCS. The use of numerical simulations aid to explore several considerations in design and analysis of a NCS.
