The foundation for our project was the work done by the active wing group of spring
2002 and the 1978 master's thesis project by Randall Bolding. A compendium of the work
done by Bolding and the spring '02 active wing group is given in this section.
2002 and the 1978 master's thesis project by Randall Bolding. A compendium of the work
done by Bolding and the spring '02 active wing group is given in this section.
2.1 Suppression of Flutter Utilizing Actively Controlled Stabilator
The 1978 master's thesis by Randall Bolding is the origins of the active wing design
project. Half of the wing-stabilator model built by Bolding is currently in the possession of
AWT. Bolding's primary use of the wing-stabilator model was to research the use of the
stabilator as an active control to suppress flutter. The design team at AWT sought to
further Bolding's work. Bolding's master's thesis has been read multiple times in an attempt
to understand the fundamental principles behind the wing-stabilator model. In particular, the
hydraulic power supply and the analog control system have been researched thoroughly.
However, the graduate level details, such as the formulation of the control laws that were
utilized to suppress flutter, were not given much attention. It is important to note that,
Bolding used the interaction between the flow about the wing and the stabilator to suppress
flutter; the stabilator was the active control. In AWT's current project, control surfaces are
considered the active controls.
project. Half of the wing-stabilator model built by Bolding is currently in the possession of
AWT. Bolding's primary use of the wing-stabilator model was to research the use of the
stabilator as an active control to suppress flutter. The design team at AWT sought to
further Bolding's work. Bolding's master's thesis has been read multiple times in an attempt
to understand the fundamental principles behind the wing-stabilator model. In particular, the
hydraulic power supply and the analog control system have been researched thoroughly.
However, the graduate level details, such as the formulation of the control laws that were
utilized to suppress flutter, were not given much attention. It is important to note that,
Bolding used the interaction between the flow about the wing and the stabilator to suppress
flutter; the stabilator was the active control. In AWT's current project, control surfaces are
considered the active controls.
2.2 Active Aeroelastic Wing
One of the main focuses of the spring '02 active wing group was to study the
applications of the actively controlled wing-stabilator model in the field of the Active
Aeroelastic Wing. The concept behind the Active Aeroelastic Wing stems from the problem
of control reversal at high airspeeds. To summarize, at large airspeeds, latent aerodynamic
forces negatively affect the actions of an aircraft's control surfaces. As an example,
consider the normal operating conditions of an airplane during rolling motion. At normal
cruise conditions one aileron is deflected up and the other is deflected down, causing the
aircraft to roll. The aircraft rolls because of an imbalance of forces on the wings of the
aircraft; the up aileron decreases the camber of one wing, which decreases the lift; the
down aileron increases the camber of the other wing, which increases the lift. Accompanying
the change in lifting forces is an axial torsion moment about each of the wings. The torsional
moment about the wing with the up aileron acts to increase the angle of attack of the wing
thus increasing the lift force; the torsional moment about the wing with the down aileron
acts to decrease the angle of attack thus decreasing the lift force. The end effect is that
the latent aerodynamic forces undermine the effectiveness of the aileron. Moreover, the
latent aerodynamic forces that result in the unwanted torsional moment increase with
airspeed. A critical airspeed exists at which deflecting the ailerons are useless; furthermore,
beyond this critical airspeed the latent aerodynamic forces are so pronounced that the
deflection of the ailerons produces the opposite effect from its intent. The idea behind
Active Aeroelastic Wing technology is to utilize the unwanted torsional moment and turn it
into a positive desired effect. Active Aeroelastic Wing technology uses active control
surfaces, such as the outboard leading edge flaps and the ailerons, to utilize the
aerodynamic forces on the twisted wing to control the aircraft. Further details are left to
the final report of the spring '02 active wing group [2].
applications of the actively controlled wing-stabilator model in the field of the Active
Aeroelastic Wing. The concept behind the Active Aeroelastic Wing stems from the problem
of control reversal at high airspeeds. To summarize, at large airspeeds, latent aerodynamic
forces negatively affect the actions of an aircraft's control surfaces. As an example,
consider the normal operating conditions of an airplane during rolling motion. At normal
cruise conditions one aileron is deflected up and the other is deflected down, causing the
aircraft to roll. The aircraft rolls because of an imbalance of forces on the wings of the
aircraft; the up aileron decreases the camber of one wing, which decreases the lift; the
down aileron increases the camber of the other wing, which increases the lift. Accompanying
the change in lifting forces is an axial torsion moment about each of the wings. The torsional
moment about the wing with the up aileron acts to increase the angle of attack of the wing
thus increasing the lift force; the torsional moment about the wing with the down aileron
acts to decrease the angle of attack thus decreasing the lift force. The end effect is that
the latent aerodynamic forces undermine the effectiveness of the aileron. Moreover, the
latent aerodynamic forces that result in the unwanted torsional moment increase with
airspeed. A critical airspeed exists at which deflecting the ailerons are useless; furthermore,
beyond this critical airspeed the latent aerodynamic forces are so pronounced that the
deflection of the ailerons produces the opposite effect from its intent. The idea behind
Active Aeroelastic Wing technology is to utilize the unwanted torsional moment and turn it
into a positive desired effect. Active Aeroelastic Wing technology uses active control
surfaces, such as the outboard leading edge flaps and the ailerons, to utilize the
aerodynamic forces on the twisted wing to control the aircraft. Further details are left to
the final report of the spring '02 active wing group [2].
2.3 Limited Cycle Oscillation
Limited cycle oscillation (LCO) is an unpredictable aerospace phenomenon because it
is induced by a variety of flight conditions of the aircraft. LCO causes the wings of the
aircraft to oscillate with limited amplitude in the vertical plane. LCO does not destroy an
aircraft; however, it induces fatigue into the structure and eventually causes failure.
Furthermore, LCO causes uncomfortable flying conditions for the pilot and could even
inhibit the ability of the pilot to accomplish his mission. The phenomenon of limited cycle
oscillation is not to be confused with classic flutter. The defining difference between LCO
and classic flutter is LCO's limited-amplitude characteristic. In classic flutter, the amplitude
of the wing oscillation diverges to infinity with catastrophic effects; however in LCO, the
wing oscillation is finite in amplitude. The amplitude of the oscillation is limited by an
unidentifiable non-linear mechanism. Figure 2 compares the bounded nature of the
amplitude of the wing tip oscillation for LCO, and the divergent nature of classic flutter.
Since, the mechanism that leads to the onset of LCO is not well understood; we cannot
accurately predict its occurrence. The system identification toolbox in Matlab will be
instrumental in developing a mathematical model of the defining equations of motion of LCO.
Once a mathematical model of LCO is determined, engineers will be able to predict its
occurrence.
is induced by a variety of flight conditions of the aircraft. LCO causes the wings of the
aircraft to oscillate with limited amplitude in the vertical plane. LCO does not destroy an
aircraft; however, it induces fatigue into the structure and eventually causes failure.
Furthermore, LCO causes uncomfortable flying conditions for the pilot and could even
inhibit the ability of the pilot to accomplish his mission. The phenomenon of limited cycle
oscillation is not to be confused with classic flutter. The defining difference between LCO
and classic flutter is LCO's limited-amplitude characteristic. In classic flutter, the amplitude
of the wing oscillation diverges to infinity with catastrophic effects; however in LCO, the
wing oscillation is finite in amplitude. The amplitude of the oscillation is limited by an
unidentifiable non-linear mechanism. Figure 2 compares the bounded nature of the
amplitude of the wing tip oscillation for LCO, and the divergent nature of classic flutter.
Since, the mechanism that leads to the onset of LCO is not well understood; we cannot
accurately predict its occurrence. The system identification toolbox in Matlab will be
instrumental in developing a mathematical model of the defining equations of motion of LCO.
Once a mathematical model of LCO is determined, engineers will be able to predict its
occurrence.
2.4 System Identification of an Arbitrary Process
The purpose of system identification is to construct a mathematical model of the
defining equations of motion of any system based on experimental data. When a system is
identified, the simulated response of the mathematical model is equal to the response of the
real-life system. Figure 3 shows an outline of the system identification process. The
system identification toolbox in Matlab is programmed to output a mathematical model of
the process given experimental data of the output in response to a given input. Through an
iterative process, Matlab determines the equations of motion representative of the true
system. The same input is given to a true system and a model system. The error is the
difference in the response between the true system and the modeled system for the same
input. When the error approaches zero, the system has been identified. The identification of
a complex system requires a numerical method, like the one utilized by Matlab, to determine
the equations of motion. However, in some cases the system is simple enough that the
equations of motion can be obtained analytically.
defining equations of motion of any system based on experimental data. When a system is
identified, the simulated response of the mathematical model is equal to the response of the
real-life system. Figure 3 shows an outline of the system identification process. The
system identification toolbox in Matlab is programmed to output a mathematical model of
the process given experimental data of the output in response to a given input. Through an
iterative process, Matlab determines the equations of motion representative of the true
system. The same input is given to a true system and a model system. The error is the
difference in the response between the true system and the modeled system for the same
input. When the error approaches zero, the system has been identified. The identification of
a complex system requires a numerical method, like the one utilized by Matlab, to determine
the equations of motion. However, in some cases the system is simple enough that the
equations of motion can be obtained analytically.
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