Conference PaperPDF Available

Rotorcraft Flight Control Design with Alleviation of Unsteady Rotor Loads

Authors:
  • U.S. Army Combat Capabilities Development Command Aviation & Missile Center
  • US Army Aviation Development Directorate - AFDD

Abstract and Figures

The objective of this paper is to develop helicopter flight control laws that minimize unsteady rotor loads while meeting desired handling qualities. These control laws are meant to act solely through the primary flight controls. First, an overview on how the harmonic decomposition methodology is used towards load alleviation control is presented. Next, explicit model following flight control laws are developed to provide insight on how the feed-forward and feedback paths can be used towards load alleviation. Their impact on the handling qualities is also studied. Finally, the control laws are optimized with CONDUIT R .
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Rotorcraft Flight Control Design with Alleviation of
Unsteady Rotor Loads
Umberto Saetti
PhD Candidate
Joseph F. Horn
Professor
Department of Aerospace Engineering
The Pennsylvania State University
University Park, PA 16802
Tom Berger
Aerospace Engineer
Mark B. Tischler
Senior Technologist
Aviation Development Directorate
CCDC Aviation & Missile Center
Moffett Field, CA
Abstract—The objective of this paper is to develop helicopter
flight control laws that minimize unsteady rotor loads while
meeting desired handling qualities. These control laws are meant
to act solely through the primary flight controls. First, an
overview on how the harmonic decomposition methodology is
used towards load alleviation control is presented. Next, explicit
model following flight control laws are developed to provide
insight on how the feed-forward and feedback paths can be
used towards load alleviation. Their impact on the handling
qualities is also studied. Finally, the control laws are optimized
with CONDUIT R
.
I. INTRODUCTION
The benefits of load alleviation control (LAC) and envelope
cueing have been demonstrated in numerous simulation stud-
ies, Refs. [1-6]. The use of Automatic Flight Control Systems
(AFCS) or active control sticks to alert the pilot to observe
structural constraints can extend the life of critical dynamic
components and reduce operating and support (O&S) costs.
These technologies can also improve handling qualities by
alleviating pilot workload associated with monitoring envelope
limits. Load alleviating controls have been implemented on the
V-22 tilt-rotor aircraft, using cyclic pitch control to reduce in-
plane loads during forward flight maneuvers [7].
Many of the critical structural limits on rotorcraft are
associated with vibratory loads and fatigue limits. These loads
are strongly influenced by higher harmonic (greater than
1/rev) dynamics in the rotor systems. These dynamics are not
modelled in the Linear Time Invariant (LTI) dynamic models
normally used for rotorcraft primary flight control design. On
the other hand, Linear Time-Periodic (LTP) models are well-
suited for representing vibratory loads on rotorcraft, including
the dominant Nb/rev vibratory forces and moments at the hub
and associated dynamic components, and they can be derived
directly from the physics-based models. Methods have been
developed for approximating LTP systems using high-order
LTI models [8], [9], [10]. The harmonic decomposition method
transforms higher frequency harmonics into states of an LTI
state space model.
The use of harmonic decomposition methods for combined
Higher-Harmonic Control (HHC)/AFCS design has been well-
0Distribution Statement A: Approved for public release.
studied in Refs. [9], [10], and has been applied towards
the design of load alleviation control and cueing methods
that act solely through the primarily flight controls (1st har-
monic swashplate control) and AFCS [11]. Recently, harmonic
decomposition models have been combined with redundant
control effectors and rotor state feedback to further improve
load alleviation [12]. Although these studies demonstrated
considerable reduction of vibratory loads in maneuvering
flight, the control action appeared to deteriorate the handling
qualities.
The objective of this paper is to thoroughly study the effect
of load alleviation on the handling qualities, and to overcome
the shortcomings of the load alleviation control design method-
ology. Specifically, the Control Designer’s Unified Interface
(CONDUIT R
) and design methods of Ref. [13] are used to
optimize controller gains to meet ADS-33E-PRF specifications
for military rotorcraft while minimizing rotor loads.
The paper is organized as follows. First, an overview
on how the harmonic decomposition methodology is used
towards the design of load alleviation control laws is presented.
Next, explicit model following control laws are developed to
understand how the feed-forward and feedback paths can be
used towards load alleviation. Their impact on the handling
qualities is also studied. The information gathered is used to
optimize the control laws to meet desired handling qualities
while minimizing rotor loads. Finally, conclusions are drawn.
II. DYNA MI CA L MOD EL
A. Nonlinear Models
This investigation uses a FLIGHTLAB R
model of a no-
tional conventional helicopter representative of a UH-60, as
shown in Fig. 1. To accurately model the rotor loads, the
model includes flexible blades with representative in-plane,
out-of-plane, and torsional bending modes, in addition to the
rigid blade flap and lag dynamics. Complete nonlinear aero-
dynamic look-up tables are used for airframe and rotor blade
aerodynamic coefficients. The inflow dynamics are described
by a six-state Peters-He inflow model. Further details on the
helicopter model are found in [1].
Fig. 1: UH-60 Black Hawk.
B. Linear Time-Periodic Model
Starting from the nonlinear model, a first order LTP system
representative of the periodic rotorcraft dynamics at 120 kts is
obtained, as demonstrated in Ref. [11]:
˙x =F(ψ)x+G(ψ)u(1a)
y=P(ψ)x+R(ψ)u(1b)
where ψis the rotor azimuth angle. The state and output
vectors of the LTP system are:
xT=xT
RB xT
R(2a)
yT=xT
RB PLL(2b)
where:
xRB are the rigid-body states,
xRare the higher-order rotor states, and
PLL is the longitudinal load of a reference pitch link.
The rigid-body state vector is given by, in order, the body
velocities u,v,w, the body angular rates p,q,r, and the Euler
angles φ,θ,ψ. The rotor states include inflow, rigid flap, lag
and torsion in multi-blade coordinates (MBC), the slowest 11
bending modes also in MBC, and the time derivatives of all
the variables in MBC. The input vector is:
uT= [δlat δlon δped](3)
where:
δlat is the lateral stick,
δlon is the longitudinal sticks, and
δped is the pedal.
The collective stick is omitted as it is not used for the
subsequent control design. The system has a total of 116 states,
14 outputs, and 3 inputs.
C. Harmonic Decomposition Model
The state, input, and output vectors of the LTP system
are decomposed into a finite number of harmonics via Fourier
analysis:
x=x0+
N
X
i=1
xic cos +xis sin (4a)
u=u0(4b)
y=y0+
L
X
i=1
yic cos +yis sin (4c)
Harmonics up to the 4th are retained for state and the output
(i.e., N=4 in Eqs. 4(a) and 4(c)). However, only the 0th
harmonic of the input vector is retained. This is because the
present study considers solely primary flight control actuation,
thus disregarding any sort of higher harmonic control. In
fact, the desired maximum bandwidth of the control signal
is significantly less than the main rotor angular speed. As
demonstrated in Ref. [9], the LTP model is transformed into
an approximate high-order LTI model:
X=AX +BU (5a)
Y=CX +DU (5b)
where:
XT=xT
0xT
1cxT
1s. . . xT
Nc xT
Ns (6a)
U=u0(6b)
YT=yT
0yT
1cyT
1s. . . yT
LcyT
Ls(6c)
are respectively the augmented state, control, and output vec-
tors.
D. Reduced-Order Model
The measurement or estimation of states associated with
the higher-order flap, lead-lag, torsion and inflow dynamics
is impractical in real applications. For this reasons, reduced-
order models are derived from the high-order LTI model. The
problem is addressed through residualization, a method based
on singular perturbation theory that accurately models low
frequency dynamics and steady-state, but neglects higher-order
dynamics [14]. The method assumes that the “fast” and stable
states in a system reach steady-state more quickly than the
“slow” states. The state vector is hence divided into fast and
slow components. The slow component comprises the rigid-
body states, whereas the fast component includes the remaining
states:
XT
s=xT
RB0(7a)
XT
f=xT
R0xT
RB1cxT
R1c
· · · xT
RB4sxT
R4s(7b)
where RB subscripts denote rigid-body states and Rsubscripts
denote rotor states. The higher-harmonics of the rigid-body
states are truncated from the output because they are impracti-
cal to observe and of negligible amplitude when compared to
their respective 0th harmonic. The output reduces to:
YT
s=xT
RB0PLL0PLL1cPLL1s· · · PLL4s(8)
Following the derivation in Ref. [11], a new reduced-order
system is obtained:
˙
Xs=ˆ
AXs+ˆ
BU (9a)
Ys=ˆ
CXs+ˆ
DU (9b)
The rotor loads are predicted with sufficient accuracy using
the 9-state approximation of the high-order LTI model, as
demonstrated in Ref. [11]. The pitch link load harmonics are
kept in the output to capture the dependence of controls and
rigid-body states on the rotor loads. This model is used in the
control design presented in the next section.
III. CON TRO LL ER DESIGN
A controller is designed to achieve stability and desired
rate-command/attitude-hold (RCAH) response around the roll,
pitch and yaw axes. The controller acts solely through primary
flight controls. This restricts the maximum desired bandwidth
of the input to be considerably less than the main rotor angular
speed. This way, higher-harmonic control is excluded. Note
that the collective stick is left open-loop. The chosen control
strategy is Explicit Model Following. The inverse plant is
based on the inverses of the following set of decoupled 1st
order linear models:
pcmd
δlatff
(s) = Lδlat
sLp
(10a)
qcmd
δlonff
(s) = Mδlon
sMq
(10b)
rcmd
δpedff
(s) = Nδped
sNr
(10c)
where the stability and control derivatives are pulled from the
9-state model. The command filters are 1st order linear models:
pcmd
δlat
(s) = kδlat
τps+ 1 (11a)
qcmd
δlon
(s) = kδlon
τqs+ 1 (11b)
rcmd
δped
(s) = kδp ed
τrs+ 1 (11c)
(11d)
where kδlat ,kδlon , and kδped are the conversion constants from
pilot commands to commanded angular rates, and τp,τq, and
τrare the command filter time constants. To each command
filter time constant corresponds a break frequency that is the
inverse of the time constant. This means that ωp= 1p,
ωq= 1q, and ωr= 1r. The commanded responses in
each axis are delayed by τφ,τθ, and τψ, respectively, for
synchronization with the (higher-order) measured responses.
These higher-order dynamics include the computational delays,
actuators, rotor flapping lag, and sensors which cannot be
included in the inverse model without causing actuator satura-
tion. The time delays are calculated following the methods of
Ref. [13]. Turn coordination and turn compensation laws are
incorporated in the feed-forward path of the control system
[15].
A linear quadratic regulator (LQR) is used for both feed-
back compensation and load alleviation. The control system
block diagram is shown in Fig. 2. The LQR gains are deter-
mined by using the 9-state model previously derived (Eq. 9).
The cost function that is minimized is:
J=Zt
0XT
sQXs+UTRU(12)
The state weighting matrix Qand control weighting matrix R
are obtained by directly constraining the output through the
following relations:
Q=ˆ
CTˆ
Qˆ
C(13a)
R=ˆ
R+ˆ
DTˆ
Qˆ
D(13b)
TABLE I: Command filter gains.
Parameter Units Value
kδlat deg/(s-%) 0.90
kδlon deg/(s-%) 0.45
kδped deg/(s-%) 36.9
where ˆ
Qand ˆ
Rare diagonal matrices. The diagonal elements
of ˆ
Qand ˆ
Rare formed by the penalties on the outputs and
inputs, respectively:
ˆ
Q= diag wT
RB wT
PLL(14a)
ˆ
R= diag (wU)(14b)
where:
wRB is the penalty vector on the rigid-body stetes,
wPLL is the penalty vector on the pitch link load harmon-
ics, and
wUis the penalty vector on the controls.
The method described allows to transfer the constraints
on each harmonic of the pitch link load response to the
rigid-body states, effectively providing a load limiting control
action based on the feedback of the 0th harmonic rigid-body
states. Most notably, the controller minimizes rotor loads
perturbations from their periodic equilibrium. It follows that
this methodology is well suited for alleviating unsteady loads.
However, it does not affect stationary (trim) loads.
IV. PARAMETRIC STUDY
This section analyzes how the feed-forward and feedback
paths of the controller can be used towards load alleviation.
Specifically, command model tailoring is examined for the
feed-forward path, whereas tailoring of the LQR weights on
the pitch link load harmonics is explored for the feedback path.
The impact of these two strategies on the handling qualities is
also studied.
First, the LQR weights are optimized with CONDUIT R
to
meet a comprehensive set of stability, handling qualities, and
performance specifications without considering load allevia-
tion. Handling qualities specifications are taken from ADS-33E
while stability margin requirements of SAE-AS94900 are used.
In particular, the weights on the rigid-body states and controls
are optimized whereas the weights on the pitch link load
harmonics are set to zero and frozen during the optimization.
The linear model used as the plant model for the optimization
is the high-order LTI model previously derived. The controller
thus obtained is referred to as the “baseline” controller. The
command filters properties for the baseline controller are found
in Tables I and II. The stability and control derivatives used
for the inverse plants are found in Table III. The equivalent
delays are shown in Table IV. The state and control penalties
are reported Tables V and VI, respectively.
Next, the closed-loop frequency responses of the pitch link
load to the commanded angular rates are computed, as shown
in Fig. 3. This is done to understand the sensitivity of the rotor
loads to pilot commands. Commanded angular rates are chosen
in favor of pilot stick commands as they share common units
Fig. 2: Control system block diagram.
TABLE II: Command filters break frequencies.
Parameter Units Value
ωprad/s 3
ωqrad/s 4.5
ωrrad/s 2
TABLE III: Stability and control derivatives.
Parameter Units Value
Lp1/s -2.9560
Mq1/s -1.3061
Nr1/s -0.3855
Lδlat rad/(s-%) 0.0976
Mδlon rad/(s-%) 0.0242
Nδped rad/(s-%) -0.1526
TABLE IV: Equivalent delays.
Parameter Units Value
τφs 0.055
τθs 0.136
τψs 0.025
(rad/s). Results are presented to cover the typical frequency
range of operation for pilots (1-60 rad/s). It appears that the
rotor loads are mostly affected by the pitch rate command in
this particular flight condition (dashed blue line in Fig. 3).
Commanded roll rate is shown to impact the rotor loads more
than the commanded yaw rate, especially at frequencies higher
than 10 rad/s. The parametric study that follows will therefore
concentrate on the roll and pitch axes.
A. Command Model Tailoring
Command filter break frequencies of the baseline controller
are varied separately for the roll and pitch axes. Figure 4 shows
the closed-loop pitch rate and pitch attitude responses to a
longitudinal stick doublet for varying command filter break
frequencies. Decreasing command filter break frequencies cor-
respond to decreasing pitch accelerations. Decreasing pitch
accelerations result in decreasing peak-to-peak pitch link loads,
as shown in Fig. 5. A running mean (or median) is obtained
by taking the sum of the maximum and minimum peaks for
each cycle and dividing by two. The curves that are plotted
are the maximum and minimum peaks minus the median.
It is concluded that command model tailoring effectively
provides load alleviation by limiting the commanded angular
acceleration.
Figure 6 shows the bandwidth and phase delay for varying
command filter break frequencies. The bandwidth and phase
delay specifications for forward flight (target acquisition and
tracking) are also reported on the plot [16]. For the roll
axis, decreasing command filter break frequencies result in
Fig. 3: Closed-loop frequency response of the the pitch link
load to the commanded angular rates.
Fig. 4: Closed-loop pitch rate and pitch attitude responses to
a longitudinal stick doublet for varying command filter break
frequencies.
decreasing bandwidth. For the pitch axis, decreasing command
filter break frequencies result in decreasing bandwidth and
increasing phase delay. In general, decreasing command filter
break frequencies appear to negatively impact the handling
qualities. It is concluded that load alleviation through feed-
forward compensation is effective in providing alleviation of
the rotor loads. However, it comes at the cost of a degradation
in the handling qualities.
B. LQR Weighting Tailoring
Starting from the baseline controller, the LQR weights on
the rigid-body states and controls are frozen while the weights
on the pitch link load harmonics are varied to generate a set of
LQR feedback gain matrices. Figure 7 provides an insight on
Fig. 5: Closed-loop peak-to-peak pitch link load response to
a longitudinal stick doublet for varying command filter break
frequencies.
Fig. 6: Bandwidth and phase delay specifications for varying
command filter break frequencies.
how the weights on the pitch link load harmonics wPLL affect
the rigid-body weights in the state penalty matrix Q. Only
the diagonal terms of the state penalty matrix are shown. It is
evident that constraining the pitch link load harmonics leads to
increased constraints on the roll and pitch rates. The pitch rate
is most affected by the 1st and 2nd cosine harmonics. The roll
rate is most affected by the 1st, 2nd, and 4th sine harmonics. In
general, the pitch rate is affected more severely than the roll
rate. This is expected and is due to the increased sensitivity
of pitch link load to pitch rate, as compared to pitch link load
to roll rate (Fig. 3). Both weights on the body velocities and
the Euler angles are unaffected. Figure 8 provides an insight
on how the weights on the pitch link load harmonics in the
output penalty matrix wPLL affect the weights on the controls
in the controls penalty matrix R. Only the diagonal terms of
the controls penalty matrix are shown. Constraining the pitch
link load harmonics leads to increased penalties mostly on the
longitudinal stick. The 0th and 1st harmonics are the major
contributors.
Figure 9 provides insight on how the weights on the pitch
Fig. 7: Gradient of the diagonal terms of the states penalty
matrix with respect to the weights on the pitch link load
harmonics.
Fig. 8: Gradient of the diagonal terms of the of the controls
penalty matrix with respect to the weights on the pitch link
load harmonics.
link load harmonics in the output penalty matrix wPLL affect
the LQR feedback gains. Only the on-axis gains are shown.
Increasing penalties on the pitch link load harmonics leads to
decreasing LQR on-axis gains. This is particularly evident for
the gains relating the longitudinal stick with pitch attitude and
pitch rate. Although not shown in the plot, the gains relating
the body velocities with the controls are largely unaffected.
These findings indicate that increasing load alleviation leads
to decreasing pitch axis performance.
Controllers with increasing weights on the pitch link load
harmonics are compared to assess the impact on handling
qualities and controller performance. Figure 10 shows the gain
and phase margins of the broken-loop response for increasing
LQR weights on the pitch link load harmonics. The stability
margin requirements defined in SAE-AS94900 are reproduced
in the plot [17]. Most notably, the roll axis gain and phase
Fig. 9: Gradient of the on-axis LQR gains with respect to the
weights on the pitch link load harmonics.
Fig. 10: Stability margins for varying LQR weights on the
pitch link load harmonics.
margins appear nearly unaffected; however, the pitch axis
gain margin increases with increasing weights. This is better
explained by looking at the crossover frequency, shown in
Fig. 11. The pitch axis crossover frequency rapidly decreases
with increasing weights. Although this leads to a higher gain
margin, it effectively results in an unsatisfactory minimum
crossover frequency [13]. The high sensitivity of the crossover
frequency to increasing LQR weights on the pitch link load
harmonics constitutes a severe limitation in the achievable load
alleviation.
Next, bandwidth and phase delay for increasing weights
on the pitch link load harmonics are shown in Fig. 12. The
bandwidth and phase delay specifications for forward flight
(target acquisition and tracking) are also reported on the plot
[16]. The roll axis bandwidth and phase delay do not appear to
be particularly affected. However, the pitch axis phase delay
decreases with increasing weights.
Figure 13 show the disturbance rejection bandwidth (DRB)
and peak (DRP) for increasing LQR weights on the pitch
link load harmonics. Similarly to the trend seen for crossover
frequency, the DRB and DRP specifications are taken from
[18] and reproduced on the plot. The DRB appears to decreases
Fig. 11: Crossover frequencies for varying LQR weights on
the pitch link load harmonics.
Fig. 12: Bandwidth and phase delay specifications for
varying LQR weights on the pitch link load harmonics.
with increasing weights on both roll and pitch axes. This leads
to a degradation of handling qualities in the pitch axis for low
weights. This poses another possible limitation in achievable
load alleviation.
The observations made for the handling qualities specifi-
cations in the frequency domain are reflected in time-domain
simulations. The closed-loop response to a longitudinal stick
Fig. 13: Disturbance rejection bandwidth (DRB) and peak
(DRP) for varying LQR weights on the pitch link load
harmonics.
Fig. 14: Closed-loop angular response to a longitudinal stick
doublet.
Fig. 15: Closed-loop peak-to-peak pitch link load response to
a longitudinal stick doublet.
doublet input is obtained for the different controllers, as shown
in Fig. 14. It is apparent that increasing LQR weights on the
pitch link harmonics effectively limits the pitch rate response,
which substantiates the findings in [12]. Figure 15 shows
the resulting load alleviation in terms of peak-to-peak pitch
link load. Since satisfactory minimum crossover frequency
and DRB for the pitch axis are obtained for minimum LQR
weights on the pitch link load harmonics (ωPLL = 1e4), the
maximum achievable load alleviation for the utility helicopter
configuration is very modest, at least for the baseline controller
that was derived.
This finding is further substantiated by the frequency
response from a disturbance in the pitch rate to the pitch
link load, as shown in Fig. 16. This particular response is
chosen because, as opposed to the response from longitudinal
stick to pitch link load, it is more representative of the
Fig. 16: Response from angular rates disturbances to pitch
link load.
feedback action only of the controller. Since pilots operate in a
frequency range of about 1-60 rad/s, considerations are made
based on that window. Indeed, the magnitude of the response
decreases for increasing LQR weights on the pitch link load
harmonics. However, weights of ωPLL = 1e4lead to a very
modest reduction. Considering the frequency response from a
disturbance in roll rate to the pitch link load, it is also observed
that increasing LQR weights on the pitch link load harmonics
do not result in any load alleviation.
In conclusion, it appears that load alleviation through
feedback compensation comes at the cost of a degradation in
the handling qualities, particularly in the pitch axis. In order
to achieve significant load alleviation while still meeting the
handling qualities requirements, a design margin optimization
of the pitch axis DRB and minimum crossover frequency
should be run on the baseline controller.
V. OPTIMIZATION RE SU LTS
An overall optimization of both the feed-forward and feed-
back paths is run in CONDUIT R
. The optimization is done in
a two-step process. First, a design margin optimization of the
pitch axis DRB and minimum crossover frequency is run on
the baseline controller. In this phase, the LQR weights on the
pitch link load harmonics are set to zero and frozen. Next, the
LQR weights on the pitch link load harmonics are optimized to
meet ADS-33E-PRF specifications while minimizing the area
under the PLL/qdist frequency response. In this second phase,
the new weights on the rigid body states and controls are frozen
and the LQR weights on the pitch link load harmonics are set
as separate optimization variables.
Figure 17 shows how the area under the PLL/qdist response
is minimized for the optimized LAC controller. This directly
translates to an alleviation in rotor loads, as shown for a pitch
rate doublet in Fig. 18. The handling qualities are all met
for the optimization controller, as shown in Fig. 19. Model
following requirements in the pitch aixs are not Level 1 as the
response of the rotorcraft is actually best modelled by a 2nd
order model in high-speed forward flight. The controller design
Fig. 17: Minimization of the angular rates disturbances to
pitch link load response.
Fig. 18: Closed-loop peak-to-peak pitch link load response to
a longitudinal stick doublet.
has to be modified accordingly. The penalties on the pitch link
load harmonics for the optimized controller are reported in
Table V. It is concluded that constraining the the rotor load
harmonics in LQR design successfully leads to load alleviation
while still meeting desired handling qualities.
VI. CONCLUSION
An overview on how the harmonic decomposition method-
ology is used towards load alleviation control was presented.
Next, explicit model following flight control laws were devel-
oped to provide insight on how the feed-forward and feedback
paths can be used towards load alleviation. Their impact on
the handling qualities was also studied. Finally, the control
laws were optimized to minimize unsteady rotor loads while
meeting desired handling qualities. Based on this work, the
following conclusions are drawn.
Fig. 19: Handling qualities for optimized LAC controller.
TABLE V: Weights on the diagonal elements of ˆ
Q.
Parameter Units Baseline LAC
uft/s 0 0
vft/s 0 0
wft/s 0 0
prad/s 1.0828e+2 1.0828e+2
qrad/s 3.8252e+2 3.8252e+2
rrad/s 2.0207e+1 2.0207e+1
φrad 6.2138e+2 6.2138e+2
θrad 1.9255e+2 1.9255e+2
ψrad 2.9349e+2 2.9349e+2
PLL0lbs 0 1.1040e3
PLL1clbs 0 2.6080e3
PLL1slbs 0 2.3360e3
PLL2clbs 0 2.2328e3
PLL2clbs 0 2.6670e3
PLL3clbs 0 1.7931e2
PLL3slbs 0 7.0606e2
PLL4clbs 0 2.3700e4
PLL4slbs 0 6.5220e3
TABLE VI: Weights on the diagonal elements of ˆ
R.
Parameter Units Baseline LAC
δlat %7.6736e2 7.6736e2
δlon %3.7561e2 3.7561e2
δped %3.0299e1 3.0299e1
1) Rotor loads in high-speed forward flight are partic-
ularly sensitive to pitch rate commands. Roll rate
commands also affect the rotor loads, but in a minor
way. Rotor loads are relatively insensitive to yaw rate
commands.
2) Load alleviation through feed-forward compensation
(command model tailoring) is effective in providing
alleviation of the rotor loads. However, it comes at the
cost of a degradation in bandwidth and phase delay.
3) Load alleviation through feedback compensation
comes at the cost of a degradation in the handling
qualities, particularly in the pitch axis. The pitch
axis disturbance rejection bandwidth (DRB) and min-
imum crossover frequency pose potential limitations
in achievable load alleviation.
4) Optimization of load alleviation flight control laws
with this methodology should be conducted in a
two-step process. First, a design margin optimization
should be run to maximize the pitch axis DRB and
minimum crossover frequency. Next, the LQR penal-
ties on the rotor loads harmonics can be optimized to
maximize load alleviation while meeting the desired
handling qualities.
5) The optimized load alleviation controller provided
load alleviation while still meeting the handling qual-
ities requirements. Constraining the higher-harmonics
of the rotor loads within an LQR architecture proved
to be an effective load alleviation strategy.
VII. ACKNOWLEDGMENTS
This research was partially funded by the Government
under Agreement No. W911W6-17-2-0003. The U.S. Gov-
ernment is authorized to reproduce and distribute reprints for
Government purposes notwithstanding any copyright notation
thereon.
The views and conclusions contained in this document are
those of the authors and should not be interpreted as repre-
senting the official policies, either expressed or implied, of the
Aviation Development Directorate or the U.S Government.
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... The inflow dynamics are described by a six-state Peters-He inflow model. Further details on the helicopter model can be found in Ref. [1], whereas model validations can be found in Ref. [19]. These validations include comparisons with the on-axis frequency responses of the U.S. Army Rotorcraft Aircrew System Concepts Airborne Laboratory JUH-60A flight-identified model at 80 kt level flight. ...
... Harmonics up to the fifth are retained for state, and harmonics up to the fourth are retained for the output [i.e., N 5 in Eq. (5a) and L 4 in Eq. (5c)], as suggested in Ref. [19]. However, only the zeroth harmonic of the input vector is retained. ...
... The flight dynamics and the rotor loads are predicted with sufficient accuracy using the nine-state approximation of the highorder LTI model, as demonstrated in extensive validation studies in Refs. [15,19]. These validation studies include time-domain (on-and off-axis response) and frequency-domain validations (input-output error, eigenvalues), and they show that the nine-state model is an accurate approximation of the high-order LTI model up to about 4 rad∕s. ...
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The objective of this research effort is to assess the impact of load alleviation control on the quantitative handling qualities specifications (also known as predicted handling qualities) of both conventional helicopters and compound rotorcraft in forward flight. First, an overview on how the harmonic decomposition methodology is used toward load alleviation control is presented. Next, flight control laws are developed based on an explicit model-following architecture. Parametric studies are performed to provide insights on how both the feedforward and feedback paths of the model-following control laws can be used to alleviate the rotor loads. The impact of load alleviation on predicted handling qualities is studied. It is shown that, for the standard helicopter configuration considered, load alleviation comes at the cost of a degradation in handling qualities. However, for the compound rotorcraft considered, allocation of the control signal to the redundant control surfaces provides load alleviation without degradation in predicted handling qualities. The flight control laws are subsequently optimized using the Control Designer’s Unified Interface (CONDUIT) to meet a comprehensive set of stability, handling-qualities, and performance specifications for specific mission task elements while minimizing the unsteady rotor loads.
... [8][9][10][11][12]), as well as in the design of load alleviation control laws (Refs. [13][14][15][16][17][18]). ...
... [9][10][11][12]) and on load alleviation control (Refs. [13][14][15][16][17][18]). However, time marching the system starting from the averaged solution may lead to an inaccurate prediction of the vehicle's periodic response. ...
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... Although conceived for military rotorcraft, ADS-33E is widely used to assess handling qualities characteristics of commercial rotorcraft as well (Refs. [54][55][56][57], as there is no counterpart in the civil domain. However, the use of ADS-33E mission task elements (MTEs) is not always relevant, especially in the design of training tasks. ...
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