a new guidance algorithm for a powered ram air parafoil ... · the-loop simulation (hils) study,...

International Journal of Applied Engineering Research ISSN 0973-4562 Volume 12, Number 18 (2017) pp. 7558-7565

© Research India Publications. http://www.ripublication.com

7558

A New Guidance Algorithm for a Powered Ram Air Parafoil System under

Wind

Tae-Wook Kim* and Yongkyu Song**

*Graduate student, Ph.D. program, ** Ph.D., Professor Department of Aerospace and Mechanical Engineering, Korea Aerospace University, Goyang City, South Korea.

Orcid ID: 0000-0001-7956-8464 **Corresponding author

Abstract

In this paper a new guidance algorithm for a powered ram air

parafoil under wind is considered. After analyzing 6 DOF and

9 DOF nonlinear dynamic models of the parafoil system, wind

effect is added to them. In order to keep the vehicle on the

desired flight path an effective guidance algorithm using

estimated wind information is proposed. After a Hardware-In-

the-Loop Simulation (HILS) study, flight tests are performed

to evaluate the new guidance algorithm under real wind.

Keywords: Powered Ram-Air Parafoil UAV, HILS

(Hardware In the Loop Simulation), Wind estimation

algorithm, Resultant Vector Guidance

INTRODUCTION

The advantage that a parafoil system can carry greater payload

compared to its weight than fixed-wing or rotary-wing aircraft

makes them useful for bulk air delivery. Because it can now

be GPS-guided to a target the parafoil system can be a good

means for civil uses such as medical or food supplies in

disaster area as well as military uses. However the parafoil

system is very susceptible to wind disturbances, which makes

it difficult to design a good autopilot for it.

Calise and Preston [1] has developed a method for

approximately correcting a guidance command for the effect

of the winds. An analysis shows that the effects of wind on

guidance loop stability are equivalent to increasing the

guidance loop gain under most flight conditions and can even

cause a sign reversal in the loop gain when the wind speed

exceeds the air speed of the vehicle. Luders et al [2] present

an on-line robust trajectory planning to execute collision

avoidance and precision landing under wind uncertainty.

Explicit real-time wind modeling and classification is used to

anticipate future disturbances and a sampling technique

ensures that robustness to possible variation is efficiently

maintained. Other most works [3-6] seek robust parafoil

terminal guidance for accurate and upwind landing under

various wind disturbances.

If a parafoil system can get wind speed and direction the

information would help to develop more capable autopilot.

However, a parafoil system assumes low cost so it is not

typically equipped with inertial systems and air data systems.

Therefore even a rough on-line estimation of wind speed and

direction would help to improve guidance performance for

flight path following. Thus in this work an effective guidance

algorithm using the approximately estimated wind speed and

direction is sought under constant horizontal wind. The

algorithm is flight tested and shows its performance.

MODELING AND HILS

Parafoil Modeling including wind

In order to design an effective guidance and control system

for a parafoil system a proper mathematical model is needed.

Based on Ref. [7] 6 DOF and 9 DOF models for a powered

parafoil system have been implemented via MATLAB

Simulink. While 6 DOF model assumes a rigid body for the

whole parafoil system, 9 DOF model adds the interaction

between canopy and payload to 6 DOF model.

Figures 1 and 2 show some simulation comparisons of 6 DOF

and 9 DOF models, where small discrepancies between

models reflect the angle (and angular rate) differences of

canopy and payload in 9 DOF model. These discrepancies do

not result in a big gap in 3D flight trajectory between two

models as in Figure 2. In this study 6 DOF model seems to

play enough role because GPS-based guidance is sought. Thus

6 DOF model including wind effect is employed in this study.

Figure 1 : Attitude Comparison of 6 DOF and 9 DOF

Modeling

mailto:[email protected]



7559

Figure 2 : 3D Flight Trajectory Comparison of 6 DOF and 9

DOF Modeling

Wind effect to a parafoil system is then included in such a

way that aerodynamic coefficients of the parafoil are

computed with wind velocity and the ground speed reflects

wind components. Wind effect has been implemented via

Simulink S-function. (Fig. 3.)

Figure 3 : Wind effect modeling

Figure 4 shows the wind effect for the three cases of wind

speed (0 m/sec, 3 m/sec, 7 m/sec) with the designated

direction. After heading to the north for 20 seconds the 25°

deflection of left control surface was applied for the later hour.

The simulation results resemble the real parafoil system.

Figure 4: Left turn under wind

(Wind 0, 3, and 7m/s)

HILS Configuration

Prior to flight tests, HILS (Hardware In the Loop Simulation)

was implemented to verify flight control system and software.

An UDP communication protocol is used to improve

communication speed and stability between MATLAB

Simulink model and HILS interface controller. (Fig. 5.)

Figure 5: Implementation of Simulink Modeling

HILS interface controller sends position, velocity, and attitude

data from Simulink model to flight control computer with

RS232 communication. HILS interface controller calculates

actuator displacement by using wire sensor and sends the

commands to Simulink model with UDP communication

protocol.



7560

Figure 6: Implementation of HILS

RAM AIR PARFOIL DESIGN & CONFIGURATION

Canopy of ram air parachute in this work was adopted from

MC-4 configuration of Ref. [8]. Aerodynamic analysis

considering 3D effect was performed with VLM (Vortex

Lattice Method) and RVLM (Ring Vortex Lattice Method)

after making applicable mesh in XFLR5 and AVL by using

exclusive parafoil design software, FW DESIGN.

Aerodynamic coefficients for the angle of attack of -3°~ 40°

were plotted with curve fitting data of AVL and XFLR5.

(Fig. 7.)

Figure 7: Ram Air Parafoil Design and Performance Analysis



7561

It is shown that Lift-Drag ratio is approximately 3 to 1 in

aerodynamic analysis of modified MC-4 canopy. For the

thrust, one 5.3KW BLDC motor with 2 blades was adopted

showing maximum thrust of 14kgf with 24 V, 20 A battery. It

is expected from the thrust test result that under the condition

of level flight with 60% thrust, battery supplies a 15 minute-

flight (Fig. 8.). Figure 9 shows the current consumption,

voltage condition, and thrust according to motor driver input

command.

To control brake line, arm type or winch type actuator is used.

Arm type has fast response but poor torque and bigger size

compared to winch type. With this reason winch type actuator

was adopted in this work.

Figure 8: Thrust test system configuration

Figure 9: Thrust system performance analysis

Table 1: Comparison of actuator drive system

Arm type Winch type

The table below shows configuration of powered ram air

parafoil.

Table 2 : Ram Air Parafoil Specifications

Specifications Ram Air Parafoil

Canopy

Model Modified MC-4

Chord(m) 1.27

Span(m) 3.22

Aspect Ratio 2.54

Inlet height(m) 0.153

Airframe

Power 5.3KW BLDC

Weight 1.2 Kgf

Actuator Type Winch Type

A NEW GUIDANCE ALGORITHM USING WIND

INFORMATION

The basic guidance algorithm to keep an aircraft on the track

between two way points is to reduce the cross track error, d, to

zero while flying to next waypoint. (Fig. 10.)



7562

Figure 10: Basic cross-track guidance

However, flight with cross track guidance algorithm without

considering wind effect will sideslip under wind as shown in

HILS (Fig. 11.). Real flight test results also show the similar

tendency as seen in Fig. 12.

In order to effectively reduce the cross-track error even under

wind this paper proposes a new guidance algorithm using

wind direction and speed information estimated by the scheme

of Ref. [9] (Fig. 13.). The algorithm estimates wind speed and

direction with only GPS measurements, and thus the relative

speed of the parafoil system to the air mass, which is equal to

the ground speed in case of no wind. The wind speed and

direction is roughly estimated once the vehicle flies more than

half circle and is assumed constant for the maneuver.

It is assumed that the relative speed to the air mass of the

parafoil system keeps constant. That is, the throttle for thrust

is fixed because the throttle change brings the altitude change

as well as the speed change, which is not desirable in the

waypoint navigation at a constant altitude. Only the heading

control using left or right flap is assumed.

Figure 11: HILS simulation results with cross-track guidance

Figure 12: Flight test trajectory with basic cross-track

guidance

Figure 13: Wind estimation algorithm

A new guidance algorithm exploiting wind information is to

make the normal component of the total ground speed to flight

path the same whether there is a wind or not (Fig. 14.).

That is, suppose that Vnet0 is the desired velocity vector

calculated by the cross-track error guidance when there is no

wind. This vector gives then the vehicle the normal

component Vnet_cross to the flight path. Our goal is to keep the

normal component of the ground speed the same even if there

is a wind velocity Vwind. To do this the heading of the parafoil

velocity vector must be rotated from (x0, y0) to(x̅, y̅). Then

the resultant vector of Vnet and Vwind becomesVtotal , which

gives the same normal component as Vnet_cross. The heading



7563

change from (x0, y0) to (x̅, y̅) can be easily computed from

vector algebra.

To evaluate the new guidance algorithm exploiting wind

information, simulations were performed together with basic

cross track guidance algorithm and the results are shown in

Figure 15. Red line shows flight trajectory obtained by the

basic cross track guidance algorithm while blue line shows

flight trajectory obtained by wind compensation algorithm.

The wind compensation guidance shows improvement on the

flight trajectory.

Figure 14 : A new guidance algorithm exploiting wind information

Figure 15 : X-track guidance HILS simulation considering wind effect



7564

FLIGHT TEST AND ANALYSIS

Flight tests were also performed to evaluate the new wind

compensation guidance algorithm. During the test wind speed

observed was 7 ~ 8 m/sec and mean wind direction was -61.2°

while there was also some gust.

The flight test was performed in one sortie, where the basic

cross-track guidance was first applied and then consecutively

new wind compensation algorithm was applied. During the

first flight (red line) wind direction and speed was also

estimated by the scheme of Kim and Song (2015) using GPS

data. Then the estimated wind direction and speed were used

to generate the new heading command for the wind

compensation guidance algorithm (blue line).

Figure 16 shows the picture of the powered ram air parafoil

and Figure 17 shows flight trajectories. While the red line

shows large deviations from the flight path line due to strong

wind, the blue line (wind compensation guidance algorithm)

shows considerable improvement in the flight path keeping.

Figure 16 : Powered Ram Air Parafoil Test Flight

Figure 17: Powered Ram Air Parafoil Autonomous Flight

trajectory

CONCLUSION

This paper presents a new wind compensation guidance

algorithm for a powered ram air parafoil system and flight

tests were performed to evaluate the algorithm. A 6 DOF

model together with wind effect is used for the simulation.

To compensate for wind effect, wind speed and direction

estimates were used in the guidance to keep the normal

component of the ground speed the same whether there is a

wind or not. The new algorithm shows considerable

improvement under real wind.

ACKNOWLEDGEMENT

This research was supported by the MSIT (Ministry of

Science and ICT), Korea, under the ITRC(Information

Technology Research Center) support program,(IITP-2017-

2014-0-00678) supervised by the IITP(Institute for

Information & communications Technology Promotion)

REFERENCES

[1] Calise, A. J. and Preston, D., “Approximate Correction

of Guidance Commands for Winds”, AIAA Paper No.

2009-2997, Proc. 20th AIAA Aerodynamic Decelerator

Systems Technology Conference and Seminar, Seattle,

Washington, 2009.

[2] Luders, B, Sugel, I., How, J. P., "Robust Trajectory

Planning for Autonomous Parafoils under Wind

Uncertainty", AIAA Infotech@Aerospace Conference,

Boston, 2013.

[3] Rogers, J., and Slegers, N., “Robust Parafoil Terminal

Guidance Using Massively Parallel Processing,” Proc.

AIAA Atmospheric Flight Mechanics Conference,

Minneapolis, Minnesota, 2012.

[4] Van der kolf, G., “Flight Control System for an

Autonomous Parafoil”, Master’s thesis, Stellenbosch

University, 2013.

[5] Ward, M., “Adaptive Glide Slope Control for Parafoil

and Payload Aircraft”, Master’s thesis, Georgia

Institute of Technology, 2012.

[6] Toolhey, D., “Development of a Small Parafoil Vehicle

for Precision Delivery, Master’s thesis, Massachusetts

Institute of Technology, 2005

[7] Slegers, N., “Effects of Canopy-Payload Relative

Motion on Control of Autonomous Parafoils,” Journal

of Guidance, Control, and Dynamics, Vol 33, No 1,

2010, pp 116-125.

[8] Eslambolchi, A., and Johari, H., "Simulation of Flow

field Around a Ram-Air Personnel Parachute Canopy",

Journal of Aircraft, Vol. 50, No. 5, 2013, pp. 1628-

1636.

http://acl.mit.edu/papers/Luders13_Infotech.pdf





7565

[9] Kim, T., and Song, Y., “A Study on the Wind

Estimation for Unmanned Parafoil System” Journal of

the korean society for aviation and aeronautics , Vol.23,

no.1, 2015, pp.8-13

[10] Benton, J. E., “Miniaturization, Integration, Flight

Testing, and Performance Analysis of a Scalable

Autonomous GPS-Guided Parafoil System for Targeted

Payload Return”, Master’s thesis, San jose State

University, 2012.

[11] Umenberger, J., “Guidance, Navigation and Control of

a Small-Scale Paramotor”, Australasian Conference on

Robotics and Automation, University of Sydney , 2012.

[12] Watanabe, M., and Ochi, Y., “Modeling and

Simulation of Nonlinear Dynamics of a Powered

Paraglider”, Proc. AIAA Guidance, Navigation and

Control Conference and Exhibit , 2008.

a new guidance algorithm for a powered ram air parafoil ... · the-loop simulation (hils) study,...

Documents