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constructed and used in order to locate a ship exactly at desired initial position. Figure 4.1: Example Ship Image(Left) and Filtered Image(Right)

Figure 4 constructed and used in order to locate a ship exactly at desired initial position. Figure 4.1: Example Ship Image(Left) and Filtered Image(Right)

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FIGURE
FIGURE
Figure 1.4: Infrared images of the cooperative object [12] be used only in the proximity of a ship since it captures the "T" mark on a landing spot.
Figure 1.4: Infrared images of the cooperative object [12] be used only in the proximity of a ship since it captures the "T" mark on a landing spot.
rotation matrices for the yaw, pitch and roll rotations are given below. a singularity at a rotation angle of +90°, this does not happen in general helicopter maneuver. The n this order. Thus, the final rotation matrix from the earth-fixed coordinate system "G" to the
rotation matrices for the yaw, pitch and roll rotations are given below. a singularity at a rotation angle of +90°, this does not happen in general helicopter maneuver. The n this order. Thus, the final rotation matrix from the earth-fixed coordinate system "G" to the
The rotation matrix from inertial to helicopter body axes is given by motions respectively. The unit vectors along the body axes are calculated by
The rotation matrix from inertial to helicopter body axes is given by motions respectively. The unit vectors along the body axes are calculated by
Figure 2.1: Earth-fixed frame and helicopter body-fixed frame
Figure 2.1: Earth-fixed frame and helicopter body-fixed frame
The rotation matrix from the helicopter body frame to the blade non-rotating frame is forward and has no lateral tilt angle. The unit vectors along the blade non-rotating frame are
The rotation matrix from the helicopter body frame to the blade non-rotating frame is forward and has no lateral tilt angle. The unit vectors along the blade non-rotating frame are
Figure 2.2: Blade non-rotating frame
Figure 2.2: Blade non-rotating frame
along the blade rotating frame are given by
along the blade rotating frame are given by
The unit vectors along the blade flapped frame are given by The rotation matrix from the blade rotating axes to the blade flapped axes is given by
The unit vectors along the blade flapped frame are given by The rotation matrix from the blade rotating axes to the blade flapped axes is given by
Figure 2.4: Blade flapped frame
Figure 2.4: Blade flapped frame
lagged frame are given by The rotation matrix from the blade flapped frame to the blade lagged frame is given by
lagged frame are given by The rotation matrix from the blade flapped frame to the blade lagged frame is given by
Figure 2.5: Blade lagged frame
Figure 2.5: Blade lagged frame
The rotation matrix from the blade non-rotating axes to the TPP axes is given by intermediate axis. The unit vectors along the TPP frame are given by
The rotation matrix from the blade non-rotating axes to the TPP axes is given by intermediate axis. The unit vectors along the TPP frame are given by
Figure 2.7: Geometry of the TPP in side view Figure 2.6: Geometry of the TPP in rear view
Figure 2.7: Geometry of the TPP in side view Figure 2.6: Geometry of the TPP in rear view
The mathematical models for loads generated by each of these components are described in the and are given by
The mathematical models for loads generated by each of these components are described in the and are given by
The longitudinal flow incidence angle ap is positive when the fuselage is tilted nose-up with re-
The longitudinal flow incidence angle ap is positive when the fuselage is tilted nose-up with re-
Fp and Mf, respectively, the loads at the vehicle center of gravity are given by
Fp and Mf, respectively, the loads at the vehicle center of gravity are given by
a flow going downward. of the airfoil and Up is positive for an outboard flow. The component Up is defined as positive for The body-fixed linear velocity components, which are u, v, and w along the 7p, jz, and kp,
a flow going downward. of the airfoil and Up is positive for an outboard flow. The component Up is defined as positive for The body-fixed linear velocity components, which are u, v, and w along the 7p, jz, and kp,
inflow ratio with respect to the blade tip speed as where the lock number ¥, the mass flapping moment of inertia J, are
inflow ratio with respect to the blade tip speed as where the lock number ¥, the mass flapping moment of inertia J, are
The hub loads are converted to the helicopter body-fixed frame using the transformation matrix contributions from individual blades. The hub force and moment components are Tgn which are the main rotor contributions to the helicopter force and moment equilibrium as are obtained by resolving the blade loads along the blade non-rotating frame and summing the blade rotating frame which contain the sum of inertial and aerodynamic loads. The hub loz
The hub loads are converted to the helicopter body-fixed frame using the transformation matrix contributions from individual blades. The hub force and moment components are Tgn which are the main rotor contributions to the helicopter force and moment equilibrium as are obtained by resolving the blade loads along the blade non-rotating frame and summing the blade rotating frame which contain the sum of inertial and aerodynamic loads. The hub loz
2.5.4 BLADE FLAPPING AND LAGGING DYNAMICS
2.5.4 BLADE FLAPPING AND LAGGING DYNAMICS
Figure 2.9: Geometry of Blade Flapping Equilibrium
Figure 2.9: Geometry of Blade Flapping Equilibrium
Integrating along the blade and dividing by 1? yields be considered as the undamped natural frequency in a spring-mass-damper system. Hence, the flapping equation can be expressed by
Integrating along the blade and dividing by 1? yields be considered as the undamped natural frequency in a spring-mass-damper system. Hence, the flapping equation can be expressed by
Figure 2.10: Geometry of Blade Lagging Equilibrium blade as it rotates. Moment equilibrium about the lead-lag hinge is expressed as
Figure 2.10: Geometry of Blade Lagging Equilibrium blade as it rotates. Moment equilibrium about the lead-lag hinge is expressed as
Integrating along the blade and dividing by 1? yields
Integrating along the blade and dividing by 1? yields
These dynamic inflow components are related to the forces on the rotor disk which are the rotor this mathematical UH-60 helicopter model, the Pitt-Peters linear inflow model is used.
These dynamic inflow components are related to the forces on the rotor disk which are the rotor this mathematical UH-60 helicopter model, the Pitt-Peters linear inflow model is used.
where a is the rotor disk tilt angle with respect to the free stream and Cy is the mass-flow parameter
where a is the rotor disk tilt angle with respect to the free stream and Cy is the mass-flow parameter
2.6.2 TAIL ROTOR DYNAMIC INFLOW center of gravity are obtained using a coordinate transformation The forces and moment components in fuselage body axes exerted by the tail rotor on the airframe The induced inflow of the tail rotor is assumed to be uniform over the disk, and is represented sing a l-state Pitt-Peters dynamic inflow model. The ODE governing the inflow dynamics is
2.6.2 TAIL ROTOR DYNAMIC INFLOW center of gravity are obtained using a coordinate transformation The forces and moment components in fuselage body axes exerted by the tail rotor on the airframe The induced inflow of the tail rotor is assumed to be uniform over the disk, and is represented sing a l-state Pitt-Peters dynamic inflow model. The ODE governing the inflow dynamics is
vehicle body axes, the angles of attack and sideslip at the tail surfaces are computed as represent the velocity components at the horizontal stabilator and vertical fin, respectively, alon;
vehicle body axes, the angles of attack and sideslip at the tail surfaces are computed as represent the velocity components at the horizontal stabilator and vertical fin, respectively, alon;
Figure 3.1: Main Rotor Power vs. Forward Flight Speed (16,360 Ibs at 3,670 feet)
Figure 3.1: Main Rotor Power vs. Forward Flight Speed (16,360 Ibs at 3,670 feet)
Figure 3.2: Fuselage Angle vs. Forward Flight Speed (16,000 Ibs at 5,250 feet)
Figure 3.2: Fuselage Angle vs. Forward Flight Speed (16,000 Ibs at 5,250 feet)
Figure 3.3: Fuselage Angle vs. Forward Flight Speed (16,000 Ibs at 5,250 feet)
Figure 3.3: Fuselage Angle vs. Forward Flight Speed (16,000 Ibs at 5,250 feet)
Figure 3.4: Fuselage Pitch Angle vs. Forward Flight Speed (16,000 Ibs at 5,250 feet)
Figure 3.4: Fuselage Pitch Angle vs. Forward Flight Speed (16,000 Ibs at 5,250 feet)
Figure 3.5: Fuselage Roll Angle vs. Forward Flight Speed (16,000 Ibs at 5,250 feet}
Figure 3.5: Fuselage Roll Angle vs. Forward Flight Speed (16,000 Ibs at 5,250 feet}
Figure 3.6: Flap and Lead-Lag Angle vs. Forward Flight Speed (16,000 Ibs at 5,250 feet)
Figure 3.6: Flap and Lead-Lag Angle vs. Forward Flight Speed (16,000 Ibs at 5,250 feet)
Figure 3.7: Inflow Ratio vs. Forward Flight Speed (16,000 Ibs at 5,250 feet)
Figure 3.7: Inflow Ratio vs. Forward Flight Speed (16,000 Ibs at 5,250 feet)
Figure 3.8: Collective Stick vs. Forward Flight Speed (16,000 Ibs at 5,250 feet)
Figure 3.8: Collective Stick vs. Forward Flight Speed (16,000 Ibs at 5,250 feet)
Figure 3.9: Longitudinal Cyclic vs. Forward Flight Speed (16,000 Ibs at 5,250 feet)
Figure 3.9: Longitudinal Cyclic vs. Forward Flight Speed (16,000 Ibs at 5,250 feet)
Figure 3.10: Lateral Cyclic vs. Forward Flight Speed (16,000 Ibs at 5,250 feet)
Figure 3.10: Lateral Cyclic vs. Forward Flight Speed (16,000 Ibs at 5,250 feet)
Figure 3.11: Pedal vs. Forward Flight Speed (16,000 Ibs at 5,250 feet)
Figure 3.11: Pedal vs. Forward Flight Speed (16,000 Ibs at 5,250 feet)
Figure 3.12: Fuselage Pitch Angle vs. Climb/Descent Angle (16,000 Ibs at 5,250 feet)
Figure 3.12: Fuselage Pitch Angle vs. Climb/Descent Angle (16,000 Ibs at 5,250 feet)
Figure 3.13: Collective Stick vs. Climb/Descent Angle (16,000 Ibs at 5,250 feet)
Figure 3.13: Collective Stick vs. Climb/Descent Angle (16,000 Ibs at 5,250 feet)
Figure 3.14: Longitudinal Cyclic vs. Climb/Descent Angle (16,000 Ibs at 5,250 feet)
Figure 3.14: Longitudinal Cyclic vs. Climb/Descent Angle (16,000 Ibs at 5,250 feet)
Figure 3.15: Lateral Cyclic vs. Climb/Descent Angle (16,000 Ibs at 5,250 feet)
Figure 3.15: Lateral Cyclic vs. Climb/Descent Angle (16,000 Ibs at 5,250 feet)
Figure 3.16: Pedal vs. Climb/Descent Angle (16,000 Ibs at 5,250 feet)
Figure 3.16: Pedal vs. Climb/Descent Angle (16,000 Ibs at 5,250 feet)
Figure 3.17: Fuselage Roll Angle vs. Turn Rate (16,000 Ibs at 5,250 feet)
Figure 3.17: Fuselage Roll Angle vs. Turn Rate (16,000 Ibs at 5,250 feet)
Figure 3.18: Fuselage Pitch Angle vs. Turn Rate (16,000 Ibs at 5,250 feet)
Figure 3.18: Fuselage Pitch Angle vs. Turn Rate (16,000 Ibs at 5,250 feet)
Figure 3.19: Collective Stick vs. Roll Angle (16,000 Ibs at 5,250 feet)
Figure 3.19: Collective Stick vs. Roll Angle (16,000 Ibs at 5,250 feet)
Figure 3.20: Longitudinal Cyclic vs. Roll Angle (16,000 Ibs at 5,250 feet)
Figure 3.20: Longitudinal Cyclic vs. Roll Angle (16,000 Ibs at 5,250 feet)
Figure 3.21: Lateral Cyclic vs. Roll Angle (16,000 Ibs at 5,250 feet)
Figure 3.21: Lateral Cyclic vs. Roll Angle (16,000 Ibs at 5,250 feet)
Figure 3.22: Pedal vs. Roll Angle (16,000 Ibs at 5,250 feet)
Figure 3.22: Pedal vs. Roll Angle (16,000 Ibs at 5,250 feet)
Figure 4.2: Overview of Detection and Positioning counts from the center of horizon to the mid-point of the bar.
Figure 4.2: Overview of Detection and Positioning counts from the center of horizon to the mid-point of the bar.
and then force them to take these values. If the desired final values of the states and control inputs rows in Cs has to be the same as the number of control inputs which is 4. In other words, it is able to give 4 non-zero reference states to track and the other states are regulated to zero at the same
and then force them to take these values. If the desired final values of the states and control inputs rows in Cs has to be the same as the number of control inputs which is 4. In other words, it is able to give 4 non-zero reference states to track and the other states are regulated to zero at the same
Figure 4.3: Entire Trajectory in diagonal view and blue line represents the helicopter trajectory.
Figure 4.3: Entire Trajectory in diagonal view and blue line represents the helicopter trajectory.
Figure 4.4: Entire Trajectory in top view
Figure 4.4: Entire Trajectory in top view
Figure 4.5: Entire Trajectory in side view
Figure 4.5: Entire Trajectory in side view
Figure 4.6: Entire Trajectory in rear view
Figure 4.6: Entire Trajectory in rear view
Figure 4.8: Final Relative Displacement Figure 4.7: Relative Displacement in time
Figure 4.8: Final Relative Displacement Figure 4.7: Relative Displacement in time
Figure 4.10: Descent Trajectory in top view
Figure 4.10: Descent Trajectory in top view
Figure 4.12: Body Axes Linear Velocity States in Descent
Figure 4.12: Body Axes Linear Velocity States in Descent
Figure 4.11: Descent Trajectory in side view
Figure 4.11: Descent Trajectory in side view
Figure 4.13: Body Axes Angular Velocity States in Descent
Figure 4.13: Body Axes Angular Velocity States in Descent
Figure 4.14: Body Axes Angular Velocity States in Descent
Figure 4.14: Body Axes Angular Velocity States in Descent
Figure 4.15: Relative Control Inputs in Descent settlement of states. In this case, it requires to begin the next maneuver (steady turn) at 30.14
Figure 4.15: Relative Control Inputs in Descent settlement of states. In this case, it requires to begin the next maneuver (steady turn) at 30.14
Figure 4.16: Steady Turn Trajectory in top view
Figure 4.16: Steady Turn Trajectory in top view
Figure 4.17: Steady Turn Trajectory in side view
Figure 4.17: Steady Turn Trajectory in side view
Figure 4.18: Body Axes Linear Velocity States in Steady Turn
Figure 4.18: Body Axes Linear Velocity States in Steady Turn
Figure 4.19: Body Axes Angular Velocity States in Steady Turn
Figure 4.19: Body Axes Angular Velocity States in Steady Turn
Figure 4.20: Euler Angle States in Steady Turn
Figure 4.20: Euler Angle States in Steady Turn
Figure 4.21: Relative Control Inputs in Steady Turn
Figure 4.21: Relative Control Inputs in Steady Turn
Figure 4.22: Deceleration Trajectory in top view
Figure 4.22: Deceleration Trajectory in top view
Figure 4.23: Deceleration Trajectory in side view
Figure 4.23: Deceleration Trajectory in side view
Figure 4.24: Body Axes Linear Velocity States in Deceleration
Figure 4.24: Body Axes Linear Velocity States in Deceleration
Figure 4.25: Body Axes Angular Velocity States in Deceleration
Figure 4.25: Body Axes Angular Velocity States in Deceleration
Figure 4.26: Euler Angle States in Deceleration
Figure 4.26: Euler Angle States in Deceleration
Figure 4.27: Relative Control Inputs in Deceleration
Figure 4.27: Relative Control Inputs in Deceleration
Figure 4.28: Landing Trajectory in top view
Figure 4.28: Landing Trajectory in top view
Figure 4.30: Body Axes Linear Velocity States in Landing
Figure 4.30: Body Axes Linear Velocity States in Landing
Figure 4.29: Landing Trajectory in side view
Figure 4.29: Landing Trajectory in side view
Figure 4.31: Body Axes Angular Velocity States in Landing
Figure 4.31: Body Axes Angular Velocity States in Landing
Figure 4.32: Euler Angle States in Landing
Figure 4.32: Euler Angle States in Landing
Figure 4.33: Relative Control Inputs in Landing
Figure 4.33: Relative Control Inputs in Landing
Figure 4.34: Visualized Ship Landing at initial position in Cockpit View latitude and longitude value. Based on this data, it visualizes the entire helicopter ship landing
Figure 4.34: Visualized Ship Landing at initial position in Cockpit View latitude and longitude value. Based on this data, it visualizes the entire helicopter ship landing
‘igure 4.35: Visualized Ship Landing at flight deck in Outside View
‘igure 4.35: Visualized Ship Landing at flight deck in Outside View
Figure 4.36: Visualized Ship Landing under bad weather in Tail View
Figure 4.36: Visualized Ship Landing under bad weather in Tail View
Figure 4.37: Visualized Ship Landing with night vision goggle (NVG) at night in Cockpit View
Figure 4.37: Visualized Ship Landing with night vision goggle (NVG) at night in Cockpit View
Related topics:
Computer VisionVisualizationMarine EngineeringVision Based NavigationTrajectory TrackingLinear Quadratic regulatorUnmanned Aerial Vehicle
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