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George Bucsan Marco Romero Nick Solarz Evan Molenda Peter Vardakas

Aircraft Rudder Servo. George Bucsan Marco Romero Nick Solarz Evan Molenda Peter Vardakas. Aircraft Rudder Servo Control. Rudder Basics Model Construction PID control and Tuning Simulink Wind Tunnel Testing CFD testing Conclusion. Project Goal.

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George Bucsan Marco Romero Nick Solarz Evan Molenda Peter Vardakas

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  1. Aircraft Rudder Servo George Bucsan Marco Romero Nick Solarz Evan Molenda Peter Vardakas

  2. Aircraft Rudder Servo Control Rudder Basics Model Construction PID control and Tuning Simulink Wind Tunnel Testing CFD testing Conclusion

  3. Project Goal The goal of the project is to analyze and develop servo control of a rudder by building a model for wind tunnel testing with Computational Fluid Dynamics (CFD) verification.

  4. Rudder Basics • In basic principle, one must understand that the rudder is not by any means the primary control system for steering an aircraft but rather helps by countering for adverse yawing motion.

  5. Rudder Basics • In a typical aircraft, the rudder is connected through mechanical linkages or hydraulics to pedals which are conveniently located beneath the pilots seat as if it were a car.

  6. Model Construction • VEX prototype • Geared motor drive • 4x4 inch control surface

  7. Aerospace Engineering and System Boundaries http://www.nitroplanes.com/81a807-asso-v71-nitroplane.html • Medium size RC plane: • 3’’ wingspan • Maximum speed ~ 30m/s (67mph) • Rudder control surface area ~ 16 sq. in.

  8. Aerospace Engineering and System Boundaries • Simplified, clean model • Easy access for attaching sensors • Cost effective

  9. Aerospace Engineering and System Boundaries

  10. Aerospace Engineering and System Boundaries • ANSYS FLUENT (C.F.D.) • Maximum torque constraint:11.34Nm @ 30m/s • Almost linear behavior 30 m/s 20 m/s 10 m/s

  11. Real World Model • Implement an actual PID controller • Test the controller within a wind tunnel • Analyze the controllers effectiveness in varying airspeeds

  12. PID Control • Proportional, Integral, and Derivative Control • Most widely used controller system in industry • Very simple to implement • Output consists of the sums of three components

  13. Proportional Gain • Proportional gain is responsible for the majority of change in a system • Responsible for the initial rise time (Transient response) • Calculated by multiplying the current error, e(t), by the gain coefficient Kp

  14. Integral Gain • Responsible for correcting steady-state error • Gain increases over time as the sum of errors accumulate • Calculated by multiplying the gain coefficient, Ki, by the error sum

  15. Derivative Gain • Responsible for system stability by preventing quick changes to the system • Calculated by multiplying the gain coefficient, Kd, by the error slope

  16. Tuning Adjusting the gain coefficients(Kp, Ki, Kd) to reach a desired criterion set (rise time, settling time, stability, etc.) Usually done by hand or systematically -Ziegler-Nichols method describes a systematic tuning approach where the gains are estimated based off the oscillation period of a proportional-only controller

  17. Simulink model

  18. Simulink Model Summing junctions. Kp, proportional gain. Kd, derivative gain. Ki, integral gain. M(s), motor transfer function. P(s), potentiometer transfer function. Integrator function. Derivative function.

  19. Building the Servo • Model Consists of a rudder powered by a continuous motor • Inputs into the system are two potentiometers • One acts as the set-point for the input into the system (sets the desired position) • Second acts as the feedback for the system, measuring the current position so error can be calculated

  20. Servo Microcontroller • “Brains” of the system • Where the actual PID loop lies • Handles the inputs and outputs of the system

  21. Wind Tunnel Testing • Placed system in wind tunnel at various speeds • Gathered position and motor output data as the input was set to various positions

  22. Wind Tunnel Results • Controller functioned adequately • Some steady-state error was noticeable at extreme rudder positions during high wind speed • Further tuning of the Ki gain would reduce this

  23. Conclusion Sources of error from basic model Play in gears rudder mounts Error seen sufficient for use in model plane Tuning depends on specific applications Next step: implement into actual aircraft

  24. Sources Sources: Benson, Tom. "Rudder - Yaw." NASA. 13 Sept. 2010. Web. 1 Feb. 2012. <http://www.grc.nasa.gov/WWW/k-12/airplane/rud.html>. "Rudder." Wikipedia, the Free Encyclopedia. 03 Jan. 2012. Web. 1 Feb. 2012. <http://en.wikipedia.org/wiki/Rudder>.

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