Moon Lander Design

Our last post showed the mission planning script for our lunar lander. The next step was to layout the lander. We did this using the BuildCADModel function in the Spacecraft Control Toolbox. The propulsion system is designed to meet the requirements of the mission plan. We use six 1 N HPGP thrusters for attitude control and one 220 N thruster for orbit maneuvers and landing. We have two HPGP tanks for the fuel. There are two cameras. One is used as a star camera for attitude determination and navigation and the second, which is articulated, is used for optical navigation, descent navigation and science. The IMU and C&DH box can bee seen in the drawing.

LunarCAD

The solar array has two degrees-of-freedom articulation. The high gain antenna is also articulated. We adapted the landing legs from the Apollo Lunar Module. The thruster layout is shown in the following figure and is done using the ThrusterLayout function in the toolbox.

LunarThruster

We get full 6 degree-of-freedom attitude control and z-axis velocity change control. We use the 220 N engine as the primary engine for landing but can also use four of the 1 N thrusters for fine terminal control.

We are working on the science payload for the mission. One experiment will be to mine helium-3 from the surface. Helium-3 would be a fuel for advanced nuclear fusion power plants and nuclear fusion propulsion systems.

Spacecraft CAD Design in the Spacecraft Control Toolbox

AutoDesk Inventor and SolidWorks are powerful software packages for the computer-aided design of spacecraft. Ultimately you need to use one of those packages for the mechanical design of your satellite, but what about the preliminary design phase when you are still determining what components you even need? The CAD software in the Spacecraft Control Toolbox can provide you with a valuable tool to do your conceptual layouts and early trade studies, and the same model can be used as the basis for disturbance analysis in later design phases.

A CAD model in SCT is built in a script which allows you to build your models algorithmically. You can call design functions, use for loops and revision-control your source code. For example, within the script you can do an eclipse analysis and compute the battery capacity. This number can generate the volume of your batteries which you can then use to size your spacecraft.

The function BuildCADModel provides the model-building interface. The CreateComponent function is used to generate the individual components using parameter pairs as arguments. Components are grouped into bodies to allow for rotation and articulation. A GUI displays your finished model and allows you to visualize it in 3D. You then store your finished models as mat-files. Our disturbance model uses every triangle in your model for disturbance analysis.

The example figure shows a solar sail design, with the spacecraft bus in the middle. BuildCADModel allows you to group components into subsystems as on the left-hand side, which can then be highlighted using transparency.

Subsystem

The figure below shows the BuildCADModel GUI which allows you to verify the body and component properties.BuildCADModel-Vehicle

There are many examples of spacecraft models in the SCT to help you get started, and a lengthy chapter in the User’s Guide discussing the finer points of component location, orientation, and physical properties such as drag and optical coefficients. Your CAD model essentially functions as a database for your entire spacecraft model!

Simulating Magnetic Hysteresis Damping

CubeSats have caused a renewed interest in magnetic control of satellites, and passive hysteresis damping in particular. Modeling actual hysteresis rods on a satellite is not trivial, and generally requires empirical data on the properties of the rods selected. Our newest CubeSat simulation demonstrates damping using rods in LEO. A permanent magnet is modeled using a constant dipole moment, and we expect the satellite to align with the magnetic field and damp. We evaluate the results by plotting the angle between the dipole and the Earth’s magnetic field and the body rates.

First, let’s verify the magnetic hysteresis model in the toolbox using the bulk material properties in orbit. We use a dipole model of the Earth’s magnetic field. The nice hysteresis curves below confirms that we are computing the derivatives of the magnetic field correctly in the body frame, which requires careful accounting of rotating coordinates. Also we stay within the saturation limits which means our magnetic flux derivatives are correct too.

Hysteresis curves from simulating magnetic hysteresis in orbit

Hysteresis curves from simulating magnetic hysteresis in orbit

We will assume the rods are 1 mm radius and 95 mm length, with rods placed perpendicular to each other and the permanent magnet. Three rods are used per axis. The apparent rod parameters are taken from the literature. The actual rods will not reach saturation while in orbit, so we will see a minor loop.

Minor loops from damping rods

Minor loops from damping rods using apparent properties

The rods produce only a small amount of damping per orbit, so we have to run for many orbits or days to see significant damping – in some passive satellites, the total time allotted for stabilization is two months! In this case we test the rods’ ability to damp the torque induced by turning on a torque rod with a dipole of 1 AM2 and allowing the CubeSat to align itself with the magnetic field, starting from LVLH pointing.

Damping in LEO using hysteresis rods

Damping in LEO using hysteresis rods

Simulating the rods is time-intensive, with a timestep of about 4 seconds required – which makes a simulation of several days on orbit take several minutes of computation. Once performance of the rods has been verified, a simple damping factor can be substituted.

This new simulation along with the functions for hysteresis rod dynamics will be in the new version of our CubeSat Toolbox, due for release in June!

References:

  1. F. Santoni and M. Zelli, “Passive magnetic attitude stabilization of the UNISAT-4 micro satellite”, Acta Astronautica,65 (2009) pp. 792-803
  2. J. Tellinen, “A Simple Scalar Model for Magnetic Hysteresis”, IEEE Transactions on Magnetics, Vol. 34, No. 4, July 1998
  3. T. Flatley and D. Henretty, “A Magnetic Hysteresis Model”, N95-27801 (NASA Technical Repoets Server), 1995

Adaptive Cruise Control

The automotive industry continues to incorporate advanced technology and control systems design into new vehicles. Features such as adaptive cruise control, lane keep assist, autonomous park assist, and adaptive lights are becoming more common in the automotive market. These exciting technologies greatly increase vehicle safety!

Adaptive cruise controls measure the distance and speed of nearby vehicles and adjust the speed of the vehicle with the cruise control to maintain safe following distances. Typically a system will use a radar that measures range, range rate and azimuth to vehicles in its field of view.

A typical situation is shown below. The car with adaptive cruise control is traveling near three additional vehicles. Two cars have been tracked for awhile but a third is passing and plans to insert itself into the space between the tracking car and one of the tracked cars. How does the cruise control keep the three cars straight?

MHTAuto

Every measurement has uncertainty. The following drawing shows the uncertainty ellipsoids for the three vehicles. As you can see they overlap so a measurement could be associated with more than one car.

UncertaintyEllipsoids

The Princeton Satellite Systems Target Tracking Module for MATLAB implements track oriented Multiple Hypothesis Testing (MHT). MHT is a Bayesian method for reliably associating measurements with tracks. The system is shown below:

MHTSystemSimplified

The system includes a powerful track pruning algorithm that eliminates the need for ad-hoc track pruning. Without track pruning the number of tracks maintained would grow exponentially. The system generates hypotheses that are collections of tracks that are consistent, that is the tracks do not share any measurements. Measurements are incorporated into tracks and tracks are propagated using Kalman Filters. The MHT system also can handle multiple sensors for automobiles with cameras and radar.

Check out what all our MATLAB toolboxes have to offer!
Core Control Toolbox
Aircraft Control Toolbox
CubeSat Toolbox
Spacecraft Control Toolbox

Brand New Free SCT Textbook Companion App for MATLAB

We are happy to announce the release of our free Textbook Companion App for MATLAB (2012b or later).  Based on four Chapter 2 walk through tutorials, the goal is to design a geostationary spacecraft, maintaining an exact orbital position, delivering a -126 dB in the Ku band, and 7 year lifetime.

app_cover

The GUI allows us to look at the results of various gravity models, summing various types of disturbances caused by the sun-angle, a basic geo-synchronous orbit simulation, and then a full simulation that incorporates the orbit, disturbances, and Control and Link parameters. app_results

The app is available on the textbook support page: http://support.psatellite.com/sct/theory_textbook.php.

 

Europa Report

Europa Report is a movie about a human mission to Europa, a moon of Jupiter, to explore the moon for signs of life. Europa has an oxygen atmosphere and a surface composed of water ice that has led to the hypothesis that there is an ocean under the ice.

Europa Report does a great job of being scientifically accurate. The spacecraft shown in the movie addresses the major issues that travelers would experience on a voyage to Jupiter. The crew section of the spacecraft is spun for artificial gravity and accommodations are made to deal with the high radiation environment around Jupiter.

Our Spacecraft Control Toolbox can be used to design the spacecraft and simulate every phase from Earth Orbit to Europa landing. We have a script for a powered Europa landing. Here are the results!

EuropaLanding

For more information about how you can design your space missions visit our Spacecraft Control Toolbox page!

IR Imaging with the Spacecraft Control Toolbox

Many spacecraft are incorporating cameras, both visible and IR, to image other nearby objects. These may be other satellites or space debris. This blog entry shows how you can simulate imaging with the Spacecraft Control Toolbox.

In this simulation a target 1U CubeSat is illuminated by several sources of radiant flux and imaged by a camera located on a chase vehicle. The CubeSat panels have different optical and thermal properties. An exploded view is shown below. The surface properties are for radiators (black), solar panels (blue) and gold foil (yellow).

SatelliteBlog

The target is located in a circular orbit and the chase vehicle is in a similar but slightly eccentric orbit. A camera is mounted on the chase vehicle. The chase vehicle keeps its camera pointed at the target. Solar radiation, earth radiation, and earth albedo illuminate the target. The motion of the two vehicles is simulated for one revolution. The target spacecraft remains between approximately 75 m and 150 m from the chase vehicle.

RelativePos

As the target and chase vehicle move in their respective orbits, the change in temperature of the target CubeSat is simulated. Each of the 6 panels are composed of two triangles. The temperatures of the panels vary based on the thermal properties of each face and the orientation of the spacecraft. The orientation affects the incoming flux for each particular face.

Temp

Solar radiation is the dominant source over the course of the simulation but earth radiation and earth albedo also effect the total flux. The solar radiation, plotted in dark blue, clearly shows the times when the earth is blocking the line of sight from the spacecraft to the sun.

Flux

A photon detector model is assumed for the IR imaging device. The following flow chart describes the imager model.

FlowCharts

The initial output observed by the imager is shown below. It should be noted that for the particular orbit and orientation initial conditions specified, the z component of the relative position is always equal to zero. This means that only the x and y panels of the cube will be visible throughout the simulation. It is possible to specify different initial conditions that would result in a z relative position, and in this case, up to three faces of the cube can be detected.

DetectIm1

We have created a video that displays the imager results as a sequence.

IRImaging

SCT Seminar – Sheffield UK

Yosef and Amanda are giving a seminar on our Spacecraft Control Toolbox in Sheffield, England on October 1, 2013. This event has been arranged through our UK distributors, MeadoTech Ltd. A big thank you goes out to Dr. Mohamed Mahmoud and Ruth Jenkinson!

Check out what our MATLAB toolboxes have to offer!
Core Control Toolbox
Aircraft Control Toolbox
CubeSat Toolbox
Spacecraft Control Toolbox

PSS MATLAB Toolbox Tutorial Videos

Over the summer we worked on developing some videos to help customers get started using our MATLAB products. Our MIT intern, James Slonaker, did a fabulous job! Come check out our Toolbox Tutorial Videos on our YouTube Channel!

http://www.youtube.com/user/PSSToolboxVideos.

If you have any feedback or suggestions for future content, please contact us at info@psatellite.com.

New PSS MATLAB Product – Core Control Toolbox

We have just released our new MATLAB product – the Core Control Toolbox (CCT). We created the Core Control Toolbox as a base product for those customers who may have interests outside of aircraft and spacecraft modeling and simulation. It features many of the general purpose functions found in our Spacecraft Control Toolbox. Like all our Toolbox products, CCT comes with complete source code. Users can view and modify any function in the toolbox to suit their particular needs. We’ve included a number of our filtering, graphics, mathematics, quaternion, robotics, and other general purpose functions.

Below one of our robotics functions is featured! The Selective Compliance Articulated Robot Arm (SCARA) is used in many industrial applications requiring assembly in a plane, like manufacturing a PC board.

SCARA

The SCARA movie shows a SCARA robot following a straight line trajectory. The trajectory is computed by a dedicated SCARA inverse kinematics routine.

Check out what CCT and our other MATLAB toolboxes have to offer!
Core Control Toolbox
Aircraft Control Toolbox
CubeSat Toolbox
Spacecraft Control Toolbox