Comprehensive System Identification of Ducted Fan UAVs - Cal Poly

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3.4 Sensor IdentificationThe identification of the sensors and their respective errors is an area that requiressome attention. Because these vehicles are unmanned they usually utilize their controlsystems in a conservative manner. Expanding the envelope of operation would bebeneficial to the overall performance and mission success. However, the small size of thevehicles leaves them susceptible to low performance sensors. Knowing the limitation ofthe components and the effects they have on the control systems is important.All of the vehicles utilize inner loop controllers to stabilize the airframe. This isusually comprised of proportional, rate, and integral feedback. This PID controller isusually adequate to control the vehicle nicely in hover and forward flight. In some cases,the need for cross feed in pitch and roll or pitch and yaw was deemed necessary due tohigh coupling and large propeller inertias. In flight test however, this provedunwarranted. The reliance on the highest performing, small-packaged, rate gyro is high.Magnetometers are used for heading determination. The accelerometers are needed fordetermination of lateral and longitudinal speed as well as vertical speed. This iscomplimented with a pressure altimeter. Ultimately, machine or synthetic vision, laserranging equipment, and other advanced telemetry would be needed for accurate positionand landing requirements. GPS with selective availability (SA) off working nominally at1 Hz was used for outer loop position control. All of these areas need to be modeled tohave a working model of the entire system (1.11).- 94 -
3.4.1 Accelerometer IdentificationModeling of typical accelerometers was done with the representative CrossbowCXL04LP3. This is the accelerometer present on the Honeywell OAV. Theaccelerometers were modeled with white noise and random bias. Figure 3.41 shows howthis was done. According to the manufacturer, the modules could report up 0.2 g of maxbias. This would be erratic and slowly switching between positive and negative. Arandom number is filtered to ensure subtle changes between positive and negative.Hysteresis was also identified to be no more than 0.1 g. The noise coming into the systemwas identified as 10 mg RMS.Figure 3.41 – Accelerometer ModelFigure 3.42 shows the noise and nonlinear effects the model has while the sensor isstationary over a period of 10 minutes.- 95 -
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Comprehensive System Identification
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APROVAL PAGETITLE:AUTHOR:Comprehens
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ACKNOWLEDGMENTSThe author would lik
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3.4.4 Magnetometer Identification..
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LIST OF FIGURESFigure 1.1 - Land Wa
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Figure 3.48 - Magnetometer Depictio
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CHAPTER 1 - INTRODUCTION AND MOTIVA
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The vehicles examined within the sc
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tunnel testing to study the charact
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Figure 1.8 - Helicopter Body Axes S
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GPSRate GyrosAccelerometersIMUInner
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CHAPTER 2 - METHODS AND TECHNIQUES2
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2.2.1 Flight Test TechniquesThere a
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manufacturer specifications are mod
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3.2 Bare-Airframe IDThe bare-airfra
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Table 3.2 - OAV Frequency Range of
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⎧ p⎫⎪ ⎪y = ⎨q⎬⎪ r ⎪
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Table 3.4 - OAV DERIVID Identified
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The identified state-space model yi
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Better sensors, at higher sampling
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Figure 3.3 - Yaw response frequency
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Figure 3.4 shows that even though t
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It can be seen that the Aerovironme
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3.2.2 Allied Aerospace MAVFlight te
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30MAGNITUDE(DB)-10-50250PHASE(DEG)5
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A 0th/2nd order transfer function i
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Figure 3.12 shows the same for the
Page 55 and 56: Techsburg) the pitching moment resp
Page 57 and 58: Table 3.11 shows that all of the di
Page 59 and 60: Figure 3.14 shows how increasing th
Page 61 and 62: the duct, the effects of the man ne
Page 63 and 64: ft-lbMu PLATFORM= 5.11ftsecThis dim
Page 65 and 66: apparent that the size of the duct
Page 67 and 68: adequate way to characterize the di
Page 69 and 70: actuators varied in size, weight, c
Page 71 and 72: It is noticeable from the figure th
Page 73 and 74: Table 3.17 - Actuator Calibration F
Page 75 and 76: Figure 2.1 shows an example frequen
Page 77 and 78: The test matrix is provided as Tabl
Page 79 and 80: frequency response curves shown in
Page 81 and 82: Table 3.22 shows that for the first
Page 83 and 84: The time delays all seemed to be ar
Page 85 and 86: 400035003000250020001500y = -13429x
Page 87 and 88: higher data rates, and tighter tole
Page 89 and 90: esponse and the response obtained f
Page 91 and 92: The time histories show that the ou
Page 93 and 94: Figure 3.31 - Magnitude Comparison
Page 95 and 96: Performing the frequency response a
Page 97 and 98: Results from STI utilizing the exac
Page 99 and 100: The fact that the rate saturated du
Page 101 and 102: Table 3.23 for the maximum rates an
Page 103 and 104: Verification of the identified mode
Page 105: from testing (3.22), it was found t
Page 109 and 110: Figure 3.43 shows that gyros were m
Page 111 and 112: 5 meter circle centered about the t
Page 113 and 114: Figure 3.46 shows the modeled fluct
Page 115 and 116: Figure 3.49 - Pressure Altimeter Mo
Page 117 and 118: Figure 4.1 - Simulink MAV ModelFigu
Page 119 and 120: Figure 4.3 - Simulink Sweep Generat
Page 121 and 122: cause a pitching moment to be exert
Page 123 and 124: Figure 4.6 - Cross Control Decoupli
Page 125 and 126: ⎡ Lp Lq Lr Lu Lv Lw0 0 0⎤⎢MpM
Page 127 and 128: It can be seen right away that the
Page 129 and 130: Figure 4.8 shows that the coherence
Page 131 and 132: CHAPTER 5 - CONCLUSIONSThe need for
Page 133 and 134: 6. Mettler, B., Tischler, M. B., an
Page 135 and 136: Appendix AOAV Proposal VehicleIdent
Page 137 and 138: DS8417 - 5V- 125 -
Page 139 and 140: HS512MG - 5V- 127 -
Page 141 and 142: DS368 - 5V- 129 -
Page 143 and 144: 94091 - 5V- 131 -
Page 145 and 146: CS-10BB - 5V- 133 -
Page 147 and 148: Appendix CActuator Generated Transf
Page 149 and 150: DS8417 - 100% - 5V- 137 -
Page 151 and 152: DS8417 - 100% - 6V- 139 -
Page 153 and 154: HS512MG - 100% - 5V- 141 -
Page 155 and 156: HS512MG - 100% - 6V- 143 -
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DS368 - 100% - 5V- 145 -
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DS368 - 100% - 6V- 147 -
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94091 - 80% - 5V- 149 -
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94091 - 80% - 6V- 151 -
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CS-10BB - 100% - 5V- 153 -
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CS-10BB - 100% - 6V- 155 -
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Appendix DActuator Time Domain Veri
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94091 5V94091 6V- 159 -
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DS368 5VDS368 6V- 161 -
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Comprehensive System Identification of Ducted Fan UAVs - Cal Poly

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