NASA Technical Reports Server (NTRS) 20020014293: Development of a Model Following Control Law for Inflight Simulation and Flight Controls Research

9 Pages·0.29 MB·English

by  NASA Technical Reports Server (NTRS)

Development of a Model Following Control Law for Inflight Simulation and Flight
Controls Research
M. Takahashi and J. Fletcher
US Army Aviation and Troop Command
NASA Ames Research Center, MS 211-2
Moffett Field, CA 94035
Abstract
The U.S. Army and NASA are currently developing the Rotorcraft Aircrew
Systems Concepts Airborne Laboratory (RASCAL) at the Ames Research Center.
RASCAL, shown in Figure 1, is a UH-60, which is being modified in a phased
development program to have a research fly-by-wire fight control system, and an
advanced navigation research platform[ 1]. An important part of the flight controls and
handling qualities research on RASCAL will be an FCS design for the aircraft to achieve
high bandwidth control responses and disturbance rejection characteristics. Initially,
body states will be used as feedbacks, but research into the use of rotor states will also be
considered in later stages to maximize agility and maneuverability. In addition to
supporting flight controls research, this FCS design will serve as the infiight simulation
control law to support basic handling qualities, guidance, and displays research.
Research in high bandwidth controls laws is motivated by the desire to improve
the handling qualities in aggressive maneuvering and in severely degraded weather
conditions. Naturally, these advantages will also improve the quality of the model
following, thereby improving the inflight simulation capabilities of the research vehicle.
High bandwidth in the control laws provides tighter tracking allowing for higher response
bandwidths which can meet handling qualities requirements for aggressive maneuvering.
System sensitivity is also reduced preventing variations in the response from the vehicle
due to changing flight conditions. In addition, improved gust rejection will result from
this reduced sensitivity. The gust rejection coupled with a highly stable system will make
more precise maneuvering and pointing possible in severely degraded weather conditions.
The difficulty in achieving higher bandwidths from the control laws in the
feedback and in the responses arises from the complexity of the models that are needed to
produce a satisfactory design. In this case, high quality models that include rotor
dynamics in a physically meaningful context must be available. A non-physical
accounting of the rotor, such as lumping the effect as a time delay, is not likely to
produce the desired results[2]. High order simulation models based on first principals are
satisfactory for the initial design phase in order to work out the control Iaw design
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concept and get an initial set of gains. These models, however, have known deficiencies, ;ii
which must be resolved in the final control law design. The error in the pitch-roll cross
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coupling is one notable deficiency[3] that even sophisticated rotorcraft models including
complex wake aerodynamics have yet to capture successfully. This error must be
accounted for to achieve the desired decoupling.
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The approach to design the proposed inflight simulation control law is based on
using a combination of simulation and identified models. The linear and nonlinear higher
order models were used to develop an explicit model following control structure. This
structure was developed to accommodate the design of control laws compliant to many of
the quantitative requirements in ADS-33C. Furthermore, it also allows for control law
research using rotor-state feedback and other design methodologies such as Quantitative
Feedback and H-Infinity. Final gain selection will be based on higher order identified
models, which include rotor degrees of freedom.
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Identified models will be employed in order to ensure a high degree of modeling
accuracy at various design points. The CIFER frequency domain identification procedure
is used [4] to obtain minimally parameterized models. The models contain explicit rotor
degrees of freedom. Models with simple flapping dynamics have been identified from
flight test data without rotor measurements, and models with more complex dynamics are
currently being identified from flight test data including rotor blade measurements.
The purpose of the paper will be three fold 1) to describe the proposed control law
structure that is being developed for RASCAL 2) to describe the identification models
being developed to allow calculation of the final set of control gains 3) to describe the
integration of the identification models in the control law design process.
The paper will first present the proposed control law structure shown in Figure 2.
The bare airframe response is dynamically decoupled using a few constant, first order,
and second order transfer functions. Once decoupled, each axis is designed according to
the structure shown in the figure for the roll axis. The inner crossover loop is structured
to facilitate setting the crossover behavior of the design, thus, this block determines most
of the performance of the feedback. This block is a modified form of the control law
structure used in Refs. [5] and [6]. The outer hold loop is a lower gain feedback to give
the system attitude hold. Once a tight attitude loop is established, roll shaping is applied
to give the desired response.
A description of the design approach to pick the gains inside of the blocks in
figure 2 will then be given followed by some representative results using linear and
nonlinear high order simulation models. A typical example is shown in Figure 3, which
shows the step response in pitch of a non linear UI-I-60 model using the control law
configured as an attitude command system. Coplotted with the standard aircraft states are
the command model states, which are being tracked by the control law.
The paper will then discuss the system identification modeling approach and the
model structures used in the identification. The identification of models including rotor
states from flight data with and without rotating system measurements will be covered. A
model structure including simple flapping dynamics which does not require rotor state
measurements is shown in Figure 4. Models with more complex rotor dynamics are
currently under development.
Identification results will be used to show the current known deficiencies in the
simulation models. An example is shown in Figure 5, which is a comparison of frequency
responses of the roll from pitch response of the open loop UH-60 from flight data, the
identified model, and two different blade element simulation models. The two simulation
models show significant errors in prediction the phase, which is expected to severely
affect the response of the closed loop system. The process of integrating the identification
models into the design process will then be discussed and results will be shown using the
identification model in the control law structure.
References
1. Aiken, E., Jacobsen, R., Eshow, M., Hindson, W., and Doane, D., "Preliminary Design
Features of the RASCAL - A NASA/Army Rotorcraft In-Flight Simulator,"
AIAA-92-4175, August, 1992.
2. Takahashi, M.D., "Rotor-State Feedback in the Design of Flight-Control Laws for a
Hovering Helicopter," J. of the Amer. Hel. Soc.. January 1994.
3. Fletcher,JayW.,"IdentificationofUH-60StabilityDerivativeModelsin Hoverfrom
FlightTestData,"49thAnnualForumoftheAmer.Hel.Soc.,St.Louis,Missouri,
May 19-21,1993.
4. Tischler,M.B.andCauffman,M.G.,"FrequencyResponseMethodforRotorcraft
SystemIdentification:FlightApplicationstoBO 105CoupledRotor/Fuselage
Dynamics,"Journal of the American Helicopter Society, Vol. 37, No 3, PP 3-17,
1992.
5. Landis H. Kenneth, and Glusman, Steven I., "Development of ADOCS Controllers
and Control Laws, Vols. 1-3," NASA CR 177339, or USAAVSCOM TR 84-A-7,
March 1985.
6. Pausder, H.J., and Bouwer, G, Von Grunhagen, W., "A Highly Maneuverable
Helicopter rnflight Simulator - Aspects of Realization," 14th European Rotorcraft
Forum, Milano, Italy, 1988.
Figure 1 - The RASCAL UI-I-60 Helicopter
Figure 2 - Model following control law structure
Figure 3 - Closed loop, nonlinear, response to a longitudinal doublet
Figure 4 -14 DOF identification model structure for the UH-60 in
Hover
Figure 5 - Roll from pitch coupling from flight data, identification
model, and simulation models
Figure 1. The RASCAL UH-60 Helicopter
Figure 2 - Model following control law structure
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