Navigation Functionalities for an Autonomous UAV Helicopter

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50 CHAPTER 4. PATH FOLLOWING CONTROL MODE Y AWyacs = rff + K y 1 δψ P IT CHyacs = K p 1 δpx + K p 2 δvx + K p 3 d dt δvx + K p � 4 δvxdt ROLLyacs = φff + K r 1δpy + K r 2δvy (4.24) T HRyacs = K t 1δpz + K t 2δvz + K t � 3 δvzdt where the K’s are the control gains, rff and φff are the feed-forward control terms resulting from the model in 4.13. The other two terms θff and Tff relative to the pitch and throttle channels have not been implemented. These channels are controlled by the feedback loop only. δψ is the heading error, δp is the position error vector (difference between the control point and helicopter position), δv is the velocity error vector (difference between target velocity and helicopter velocity). Adding the feed forward control terms, especially on the roll channel, results in a great improvement in the tracking capability of the control system compared to a PID feedback loop only. Results of the control approach are shown in the next section. 4.4 Experimental results This section presents experimental results of the PFCM implemented on the RMAX helicopter. In Fig. 4.9, a 3D path is flown starting from an altitude of 40 meters and finishing at 10 meters. The path describes a descending spiral and the velocity vcruise given by the path planner was set to 10 m/s. In Fig. 4.10, the velocity profile of the path is represented and it can be observed that as soon as the helicopter reaches 10 m/s it slows down in order to make the turn with the compatible velocity. This was an early test, where the roll angle limitation was quite strict (around 8 deg). This explains the consistent decreasing velocity. In addition, the acceleration phase was missing. In fact, the commanded target velocity, represented by the dashed line, starts at 10 m/s. This resulted in an abrupt pitch input at the beginning of the flight. Results of several trials of the same path flown with different wind conditions are shown in Paper I.
4.4. EXPERIMENTAL RESULTS 51 Up [m] 60 50 40 30 20 10 0 B 0 −10 −20 −30 −40 −50 −60 −70 −80 −90 North [m] −100 −10 A 0 10 East [m] Figure 4.9: Target and actual 3D helicopter path. Speed [m/s] 12 10 8 6 4 2 0 490 495 500 505 510 515 520 525 Time [sec] 20 30 40 flight test target Figure 4.10: Target and actual helicopter speed. 50 Flight Test Target
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Linköping Studies in Science and T
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Acknowledgements This work would ha
Page 9 and 10: Contents 1 Introduction 1 2 Overvie
Page 11 and 12: Chapter 1 Introduction An Unmanned
Page 13 and 14: of the environment in order to avoi
Page 15 and 16: Chapter 2 Overview This chapter pre
Page 17 and 18: 2.1. UAV SOFTWARE ARCHITECTURE 7 wh
Page 19 and 20: 2.2. THE UAV HELICOPTER PLATFORM 9
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Page 23 and 24: Chapter 3 Simulation 3.1 Introducti
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Page 35 and 36: 3.5. SIMULATION RESULTS 25 Figure 3
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Page 39 and 40: Chapter 4 Path Following Control Mo
Page 41 and 42: 4.2. TRAJECTORY GENERATOR 31 Figure
Page 43 and 44: 4.2. TRAJECTORY GENERATOR 33 Fig. 4
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Page 49 and 50: 4.2. TRAJECTORY GENERATOR 39 radius
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Page 65 and 66: 4.5. CONCLUSIONS 55 Vel [m/s] 20 18
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Page 71 and 72: 5.1. FILTER ARCHITECTURE 61 filter
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Page 83 and 84: BIBLIOGRAPHY 73 [9] E. Frazzoli. Ro
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Page 89 and 90: A.1. PAPER I 79 The reference point
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A.3. PAPER III 101 yes Tbo > Tlim2
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A.3. PAPER III 103 immediately afte
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A.3. PAPER III 105 altitude [m] 20
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A.3. PAPER III 107 Fig. 10. Flight
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Department of Computer and Informat
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No 598 Rego Granlund: C 3 Fire - A
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No 1024 Aleksandra Tešanovic: Towa
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Navigation Functionalities for an Autonomous UAV Helicopter

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