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| F/A-18 Carrier Landing Architecture |
Unmanned F/A-18 Aircraft Landing Control on Aircraft Carrier in Adverse Conditions
Electrical Engineering and Systems Science > Systems and Control
[Submitted on 8 Nov 2024]
Carrier landings are a difficult control task due to wind disturbance and a changing trajectory. Demand for carrier-based drones is increasing. A robust and accurate landing control system is crucial to meet this demand. Control performance can be improved by using observers to estimate unknown variables and disturbances for use in feedback.
This paper applies a nonlinear observer to estimate the combined disturbance in the pitch dynamics of an F/A-18 during carrier landing. Additionally, controllers to regulate the velocity, rate of descent and vertical position are designed.
A full model, including the nonlinear flight dynamics, controller, carrier deck motion, wind and measurement noise is modelled in software. Combined with proportional derivative control, the proposed pitch control method is shown to be very effective converging 85% faster than a PID controller. The simulations, verify that the pitch controller can quickly track a time-varying reference despite noise and disturbances.
Submission history
From: Xinhua Wang [view email][v1] Fri, 8 Nov 2024 09:50:13 UTC (1,167 KB)
Summary
Two papers co-authored by Xinhua Wang tackle the challenge of autonomous aircraft landing on
moving marine vessels, but approach it from different perspectives - one
for rotary wing (quadrotor) and one for fixed wing (F/A-18) aircraft.
Both demonstrate successful control strategies for dealing with wind
disturbances and vessel motion, though with different technical
approaches suited to their respective aircraft types.
First Paper "Unmanned F/A-18 Aircraft Landing Control on Aircraft Carrier in Adverse Conditions"
This paper addresses the challenge of landing unmanned fixed-wing aircraft on carriers. Key points:1. Problem: Carrier landings are extremely challenging due to small runway size, deck motion, and wind disturbances
2. Solution:
- - Developed nonlinear observer to estimate pitch disturbances
- - Created controllers for velocity, descent rate and vertical position
- - Implemented complete model including flight dynamics and deck motion
- - Combined proportional derivative control with disturbance estimation
- - Modeled full F/A-18 dynamics including aerodynamics
- - Incorporated realistic ship motion, wind effects, and sensor noise
- - Compared performance against traditional PID control
- - New controller converged 85% faster than traditional PID
- - Showed robust performance tracking varying trajectories despite disturbances
- - Successfully tracked constant sink rates within 1 second
- - Some limitations noted in guidance controller performance
Second Paper - Agile UAV landing control on moving ship in adverse conditions.
Mordaunt, J., & Wang, X. (2024). Aerospace Engineering, University of Nottingham, UK. arXiv:2411.05445v1
ABSTRACT
This paper presents an agile Unmanned Aerial Vehicle (UAV) landing control by considering the effect of ship's oscillations and moving, and also disturbance (i.e., crosswind) is considered. The presented control system can make the quadrotor UAV autonomously land whilst overcoming these adverse conditions, and the addition of a rudder beneath each propeller is designed to increase the yaw authority which is found to be lacking in heavy-lift quadrotor UAV. The PID flight control system is proposed based on reference-point tracking, allowing the UAV to follow any desired path in 3D space whilst simultaneously yawing to face any desired heading. Realistic saturation limits on actuator outputs to ensure the real-world performance of actuators. Disturbances include randomised gusting wind in 3 axes, and sensor noise on translation and rotation signals to represent noise from the GPS and accelerometer respectively. The results from the simulations demonstrate that the UAV is capable of landing on a ship which is moving with varying heading and oscillating vertically on ocean waves and has the ability to time its descent such that it meets the ship at the peak of a wave to minimise the relative velocity.This paper focuses on developing a control system for landing a quadrotor UAV on a moving ship in challenging conditions. Key points:
- Problem: Landing helicopters on ships is dangerous due to wind disturbance and ship oscillations from ocean waves
- Solution:
- Developed a PID flight control system for autonomous landing
- Added rudders beneath each propeller to improve yaw control
- Implemented reference-point tracking to follow 3D paths
- Created a system to time descent with ship's wave motion
- Testing:
- Used realistic simulations including wind gusts, sensor noise, and ship movement
- Incorporated actual physical limits of actuators
- Tested in various scenarios including ship motion and crosswinds
- Results:
- Successfully landed with 0.110m position error
- Achieved relative velocity of 0.963 m/s vs target of 1.0 m/s
- System demonstrated capability to time descent to meet ship at wave peaks
- Performance deemed sufficient to replace manned helicopters for certain missions
Comparison
Let me analyze how the two landing approaches differ:
Key Differences:
1. Aircraft Dynamics and Control Challenges:
Helicopter (Quadrotor) Landing:
- Uses PID control for reference-point tracking
- Main innovation is adding rudders beneath propellers to improve yaw control
- Primary control variables are thrust and rotor speeds
- Deals with underactuation by coordinating 4 rotors for movement
- Can hover and descend vertically
F/A-18 Carrier Landing:
- More complex aerodynamics requiring nonlinear observer system
- Must maintain forward motion (cannot hover)
- Uses elevator control for pitch dynamics
- Requires precise glide slope maintenance
- More sensitive to wind disturbances due to lift dependence
2. Control Architecture:
Helicopter:
- Direct position control using PID
- Landing controller focuses on timing descent with wave peaks
- Simpler control hierarchy due to ability to hover
- Uses reference point tracking to follow path in 3D space
F/A-18:
- Multi-layer control architecture:
* Flight path generator creates ideal approach path
* Guidance controller converts position error to sink rate command
* Sink controller converts sink rate to pitch angle command
* Pitch controller manages elevator deflection
* Separate velocity controller maintains airspeed via thrust
- Uses nonlinear observer to estimate and compensate for disturbances
3. Landing Approach:
Helicopter:
- Can maintain stationary position above deck
- Waits for optimal wave position before vertical descent
- More flexible in approach path
- Focus on minimizing relative velocity at touchdown
F/A-18:
- Must maintain constant forward motion
- Follows specific glide slope approach
- More constrained landing path
- Requires precise timing and positioning
- Must coordinate speed, sink rate, and position simultaneously
4. Performance Metrics:
Helicopter:
- Position error: 0.110m
- Relative velocity at touchdown: 0.963 m/s
- Emphasis on position accuracy and controlled descent
F/A-18:
- Focus on pitch control performance
- 85% faster convergence than traditional PID
- Achieved sink rate convergence within 1 second
- Some limitations in guidance controller noted
5. Innovation Focus:
Helicopter:
- Mechanical innovation (rudders for yaw control)
- Timing-based landing strategy
- Reference point tracking system
F/A-18:
- Advanced observer-based control system
- Nonlinear disturbance estimation
- Multi-layer control architecture
- Integration of aerodynamic considerations
The key distinction is that the F/A-18 solution requires a more complex control hierarchy due to the constraints of fixed-wing flight, while the helicopter solution can take advantage of the aircraft's ability to hover and descend vertically. The F/A-18 approach focuses more on sophisticated control theory (nonlinear observers, disturbance estimation) while the helicopter approach emphasizes mechanical improvements and timing-based control strategies.
Both solutions are innovative in their respective domains, but they tackle fundamentally different physical challenges due to the distinct nature of fixed-wing versus rotary-wing aircraft operations.
Key Differences:
1. Aircraft Dynamics and Control Challenges:
Helicopter (Quadrotor) Landing:
- Uses PID control for reference-point tracking
- Main innovation is adding rudders beneath propellers to improve yaw control
- Primary control variables are thrust and rotor speeds
- Deals with underactuation by coordinating 4 rotors for movement
- Can hover and descend vertically
F/A-18 Carrier Landing:
- More complex aerodynamics requiring nonlinear observer system
- Must maintain forward motion (cannot hover)
- Uses elevator control for pitch dynamics
- Requires precise glide slope maintenance
- More sensitive to wind disturbances due to lift dependence
2. Control Architecture:
Helicopter:
- Direct position control using PID
- Landing controller focuses on timing descent with wave peaks
- Simpler control hierarchy due to ability to hover
- Uses reference point tracking to follow path in 3D space
F/A-18:
- Multi-layer control architecture:
* Flight path generator creates ideal approach path
* Guidance controller converts position error to sink rate command
* Sink controller converts sink rate to pitch angle command
* Pitch controller manages elevator deflection
* Separate velocity controller maintains airspeed via thrust
- Uses nonlinear observer to estimate and compensate for disturbances
3. Landing Approach:
Helicopter:
- Can maintain stationary position above deck
- Waits for optimal wave position before vertical descent
- More flexible in approach path
- Focus on minimizing relative velocity at touchdown
F/A-18:
- Must maintain constant forward motion
- Follows specific glide slope approach
- More constrained landing path
- Requires precise timing and positioning
- Must coordinate speed, sink rate, and position simultaneously
4. Performance Metrics:
Helicopter:
- Position error: 0.110m
- Relative velocity at touchdown: 0.963 m/s
- Emphasis on position accuracy and controlled descent
F/A-18:
- Focus on pitch control performance
- 85% faster convergence than traditional PID
- Achieved sink rate convergence within 1 second
- Some limitations in guidance controller noted
5. Innovation Focus:
Helicopter:
- Mechanical innovation (rudders for yaw control)
- Timing-based landing strategy
- Reference point tracking system
F/A-18:
- Advanced observer-based control system
- Nonlinear disturbance estimation
- Multi-layer control architecture
- Integration of aerodynamic considerations
The key distinction is that the F/A-18 solution requires a more complex control hierarchy due to the constraints of fixed-wing flight, while the helicopter solution can take advantage of the aircraft's ability to hover and descend vertically. The F/A-18 approach focuses more on sophisticated control theory (nonlinear observers, disturbance estimation) while the helicopter approach emphasizes mechanical improvements and timing-based control strategies.
Both solutions are innovative in their respective domains, but they tackle fundamentally different physical challenges due to the distinct nature of fixed-wing versus rotary-wing aircraft operations.
Tables and Figures
Here's a breakdown of figures and tables from both papers:
Figures:
Tables:
Paper 2: Unmanned F/A-18 Aircraft Landing Control on Aircraft Carrier
Figures:
Paper 1: Agile UAV landing control on moving ship in adverse conditions
Figures:
1. Coordinate system and forces - Shows basic quadrotor structure and force layout
2. Euler rotations on a body - Demonstrates sequence of rotation transformations
3. PID controller block diagram - Basic control system structure
4. First-order transfer function filtering performance - Shows noise filtering capability
5. Schematic view of propeller-rudder arrangement - Details new rudder concept
6. Control loop layout for ψ - Shows yaw control system
7. Two options for crossing North - Illustrates path options for heading changes
8. Flowchart showing method to correct ψ error - Details heading correction logic
9. Flowchart showing landing controller logic - Explains landing decision process
10. Flow of air generated by propeller over rudder - CFD simulation visualization
11. Horizontal force on rudder vs angle and speed - CFD analysis results
12. Parameter sweep results for optimal ωc values - Filter optimization results
13. Controller performance following Lissajous curve - Path tracking demonstration
14. Controller performance following spiral climb - Another tracking demonstration
15. Controller performance holding position - Hover stability demonstration
16. UAV performing landing on moving ship - Shows complete landing sequence
17. Landing controller timing descent with wave - Demonstrates wave synchronization
2. Euler rotations on a body - Demonstrates sequence of rotation transformations
3. PID controller block diagram - Basic control system structure
4. First-order transfer function filtering performance - Shows noise filtering capability
5. Schematic view of propeller-rudder arrangement - Details new rudder concept
6. Control loop layout for ψ - Shows yaw control system
7. Two options for crossing North - Illustrates path options for heading changes
8. Flowchart showing method to correct ψ error - Details heading correction logic
9. Flowchart showing landing controller logic - Explains landing decision process
10. Flow of air generated by propeller over rudder - CFD simulation visualization
11. Horizontal force on rudder vs angle and speed - CFD analysis results
12. Parameter sweep results for optimal ωc values - Filter optimization results
13. Controller performance following Lissajous curve - Path tracking demonstration
14. Controller performance following spiral climb - Another tracking demonstration
15. Controller performance holding position - Hover stability demonstration
16. UAV performing landing on moving ship - Shows complete landing sequence
17. Landing controller timing descent with wave - Demonstrates wave synchronization
Tables:
1. Quadrotor physical parameters - Lists key physical constants
2. Controller parameter saturation limits - Shows control system constraints
3. PID gains - Lists tuned controller parameters
4. Mean 3D position error - Compares performance across scenarios
5. Simulation parameters - Details test configuration values
2. Controller parameter saturation limits - Shows control system constraints
3. PID gains - Lists tuned controller parameters
4. Mean 3D position error - Compares performance across scenarios
5. Simulation parameters - Details test configuration values
Paper 2: Unmanned F/A-18 Aircraft Landing Control on Aircraft Carrier
Figures:
1. Simple schematic of carrier landing - Basic overview of landing scenario
2. Typical carrier landing architecture - Shows control system structure
3. Aircraft longitudinal plane - Illustrates aircraft forces and coordinates
4. F/A-18 Aerodynamic coefficients - Shows lift/drag characteristics
5. Trim flowchart - Process for determining trim conditions
6. Nonlinear v Linear Open-Loop step response - Model validation
7. Landing point z-motion - Shows ship deck movement
8. x-axis wind 400m behind deck - Illustrates wind disturbance model
9. Control architecture - Details complete control system
10. Pitch step response without noise or wind - Controller performance in ideal conditions
11. Pitch step response with noise and wind - Controller performance with disturbances
12. Elevator deflection during step response - Shows control surface behavior
13. Sink rate error and trajectory - Demonstrates descent control
14. Position error approaching carrier - Shows guidance performance
15. Pitch angle response on approach - Shows pitch tracking during landing
2. Typical carrier landing architecture - Shows control system structure
3. Aircraft longitudinal plane - Illustrates aircraft forces and coordinates
4. F/A-18 Aerodynamic coefficients - Shows lift/drag characteristics
5. Trim flowchart - Process for determining trim conditions
6. Nonlinear v Linear Open-Loop step response - Model validation
7. Landing point z-motion - Shows ship deck movement
8. x-axis wind 400m behind deck - Illustrates wind disturbance model
9. Control architecture - Details complete control system
10. Pitch step response without noise or wind - Controller performance in ideal conditions
11. Pitch step response with noise and wind - Controller performance with disturbances
12. Elevator deflection during step response - Shows control surface behavior
13. Sink rate error and trajectory - Demonstrates descent control
14. Position error approaching carrier - Shows guidance performance
15. Pitch angle response on approach - Shows pitch tracking during landing
Tables:
1. Nomenclature - Defines variables and symbols
2. Constants - Lists physical parameters for F/A-18
3. Trim variables - Shows equilibrium flight conditions
2. Constants - Lists physical parameters for F/A-18
3. Trim variables - Shows equilibrium flight conditions
Both papers use figures effectively to illustrate:
1. Physical system layout and coordinate systems
2. Control system architectures
3. Performance results
4. Analysis of specific components (rudder design, aerodynamics)
5. Validation of their approaches
2. Control system architectures
3. Performance results
4. Analysis of specific components (rudder design, aerodynamics)
5. Validation of their approaches
The F/A-18 paper focuses more on aerodynamics and control theory diagrams, while the quadrotor paper includes more practical demonstration figures and CFD analysis. Both use tables to document important system parameters and performance metrics.
Author
Xinhua Wang [ Google Scholar ] earned his Ph.D. from the College of Automation Engineering at Nanjing University of Aeronautics and Astronautics,Nanjing,China.Currently,he serves as an Associate Professor at the school of Automation Engineering.He was an Academic Visitor at Louisiana State University,USA,from September 2004 to July 2005.His research interests encompass unmanned systems,multi-agent mission planning,and flight control.
Carrier Landing Solution
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