Navigation Functionalities for an Autonomous UAV Helicopter

4.5. CONCLUSIONS 53
1 + s 1
C(s) = K(α ) + KI
1 + αs s
(4.25)
The phase lead compensation increases the bandwidth and, hence, makes
the closed loop system faster, but it also increases the resonance frequency
with the danger of undesired amplification of system noise. The control
system has been tuned in simulation but a second tuning iteration was
needed on the field due to the presence of damped oscillations on the roll
channel.
An experimental comparison between the modified control system and
the previous one is shown in Fig. 4.12. The target velocity in both cases
was set to 10 m/s. Fig. 4.13 depicts the target velocity and the actual
helicopter velocity relative to the path on the right side of Fig. 4.12. The
diagram on the right side in Fig. 4.12 depicts the path flown with the basic
PFCM controller (Fig. 4.11 a). One can observe that in the dynamic part
of the path, where the curvature changes rapidly, the controller is slow.
This results in a relevant tracking error.
The diagram on the left in Fig. 4.12 depicts a test of the same path
flown with the modified roll control loop (Fig. 4.11 b). The new lateral
control scheme improves the tracking capability in the presence of fast
curvature change. The helicopter can follow the dynamic part of the path
with considerably lower tracking error.
4.5 Conclusions
The PFCM developed here has been integrated in the helicopter software
architecture and it is currently used in a number of flight missions carried
out in an urban area used for flight-tests. The goal has been the development
of a reliable and flexible flight mode which could be integrated
robustly with a path planner. Safety mechanisms have been built-in the
PFCM in order to handle communication failures with the path planner
(this can happen since the path planner is implemented on a separate computer).
More details on this topic can be found in Paper I. Moreover, since
the path planner was developed before the PFCM, a number of constraints