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The Development of Neural Network Based System Identification ...

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196 CHAPTER 7 FLIGHT CONTROL SYSTEM DESIGN: RESULTS AND DISCUSSION<br />

Figure 7.7<br />

<strong>The</strong> 4 DOF NNAPC controller with recursive NN training in action.<br />

Table 7.6<br />

<strong>The</strong> final controller settings for the hovering flight test.<br />

Tuning Parameters Symbol Value<br />

State Cost Q C T C<br />

Control Cost r w 1.5<br />

Control Horizon N c 3<br />

Prediction Horizon N p 10<br />

Roll-Pitch Amplitude Constraints u max,min ± 1<br />

Yaw/Altitude Rate Constraints ∆u max,min ± 0.01<br />

Yaw Rate Gain K Ψ 1.00<br />

Altitude Speed Gain K w 0.75<br />

in action. <strong>The</strong> step response is maintained for ∼600 samples, which equals 19.8 s at a<br />

sample period time <strong>of</strong> 33 ms.<br />

Figure 7.8 and 7.9 show the output responses <strong>of</strong> the 4 DOF controllers in term <strong>of</strong><br />

the pitch angle, roll angle, yaw rate and altitude speed, together with the corresponding<br />

control signals. Table 7.7 summarises the performance indicators <strong>of</strong> the controller<br />

responses. <strong>The</strong> MSE value is calculated in the period after the steady state condition<br />

is obtained. <strong>The</strong> settling time is calculated after initiation <strong>of</strong> the step response with<br />

settling threshold <strong>of</strong> 15 %. Again, the overshoot is determined as the percentage <strong>of</strong> the<br />

highest peak compared with the settling point, and the rise time is calculated as the<br />

time taken by the response signal to rise between 10 % and 90 % <strong>of</strong> the step input value.<br />

It can be seen from visual inspection <strong>of</strong> the controller responses and the performance

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