X y z Body frame Goal vector y x y Body frame Goal vector x z Body frame Goal vector x Body frame.

Slides:



Advertisements
Similar presentations
UNIT 6 (end of mechanics) Universal Gravitation & SHM.
Advertisements

PHY126 Summer Session I, 2008 Most of information is available at:
Accounting for Angular Momentum Chapter 21. Objectives Understand the basic fundamentals behind angular momentum Be able to define measures of rotary.
© 2011 Autodesk Freely licensed for use by educational institutions. Reuse and changes require a note indicating that content has been modified from the.
Rotational Motion Chapter Opener. Caption: You too can experience rapid rotation—if your stomach can take the high angular velocity and centripetal acceleration.
Beams and Frames.
Orbital Operations – 2 Rendezvous & Proximity Operations
ARO309 - Astronautics and Spacecraft Design Winter 2014 Try Lam CalPoly Pomona Aerospace Engineering.
ATMOSPHERIC REENTRY TRAJECTORY MODELING AND SIMULATION: APPLICATION TO REUSABLE LAUNCH VEHICLE MISSION (Progress Seminar Presentation - 2) K. Sivan (Roll.
Wednesday, Oct. 26, 2005PHYS , Fall 2005 Dr. Jaehoon Yu 1 PHYS 1444 – Section 003 Lecture #16 Wednesday, Oct. 26, 2005 Dr. Jaehoon Yu Charged Particle.
Kedrick Black1 ECE 5320 Mechatronics Assignment #1 Torque Coils/Rods and Reaction Wheels Kedrick Black.
Attitude Determination and Control
Rotational Motion – Part II
Nazgol Haghighat Supervisor: Prof. Dr. Ir. Daniel J. Rixen
Attitude Estimation Thomas Bak Institute of Electronic Systems
 Background  Problem Statement  Solution  Mechanical › Azimuth › Elevation › Concepts › Static and Dynamics of System  Software › SatPC32 › Interpolation.
Feasibility of Demonstrating PPT’s on FalconSAT-3 C1C Andrea Johnson United States Air Force Academy.
Introduction What is this ? What is this ? This project is a part of a scientific research in machine learning, whose objective is to develop a system,
Single Point of Contact Manipulation of Unknown Objects Stuart Anderson Advisor: Reid Simmons School of Computer Science Carnegie Mellon University.
Single-view geometry Odilon Redon, Cyclops, 1914.
Announcements WebAssign HW Set 5 due October 10
Wednesday, 11/05/14 TEKS: P.4C: Analyze and describe accelerated motion in two dimensions using equations, including projectile and circular examples.
Game Physics – Part IV Moving to 3D
Rigid Body: Rotational and Translational Motion; Rolling without Slipping 8.01 W11D1 Today’s Reading Assignment Young and Freedman: 10.3.
SVY 207: Lecture 4 GPS Description and Signal Structure
1 Project Name Solar Sail Project Proposal February 7, 2007 Megan Williams (Team Lead) Eric Blake Jon Braam Raymond Haremza Michael Hiti Kory Jenkins Daniel.
Parallel Programming Models Jihad El-Sana These slides are based on the book: Introduction to Parallel Computing, Blaise Barney, Lawrence Livermore National.
When Existence is Enough Dan Kalman American University.
Announcements WebAssign HW Set 6 due this Friday Problems cover material from Chapters 19 Prof. Kumar tea and cookies today from 5 – 6 pm in room 2165.
Complete Pose Determination for Low Altitude Unmanned Aerial Vehicle Using Stereo Vision Luke K. Wang, Shan-Chih Hsieh, Eden C.-W. Hsueh 1 Fei-Bin Hsaio.
Disturbance Rejection: Final Presentation Group 2: Nick Fronzo Phil Gaudet Sean Senical Justin Turnier.
Dynamics Modeling and First Design of Drag-Free Controller for ASTROD I Hongyin Li, W.-T. Ni Purple Mountain Observatory, Chinese Academy of Sciences S.
Modern Navigation Thomas Herring
1 7/26/04 Midterm 2 – Next Friday (7/30/04)  Material from Chapters 7-12 I will post a practice exam on Monday Announcements.
Effect of Structure Flexibility on Attitude Dynamics of Modernizated Microsatellite.
ENGR 214 Chapter 17 Plane Motion of Rigid Bodies:
Week 13 - Monday.  What did we talk about last time?  Exam 2!  Before that…  Polygonal techniques ▪ Tessellation and triangulation  Triangle strips,
Thursday, Nov. 3, 2011PHYS , Fall 2011 Dr. Jaehoon Yu 1 PHYS 1444 – Section 003 Lecture #18 Thursday, Nov. 3, 2011 Dr. Jaehoon Yu Torque on a Current.
University of Colorado Boulder ASEN 5070: Statistical Orbit Determination I Fall 2014 Professor Brandon A. Jones Lecture 18: Minimum Variance Estimator.
Why Design Tool? 93 年 10 月 21 日. EPS Course - 2 Simple Problems Close form solution Complex Problems Computer.
Announcements WebAssign HW Set 5 due October 10 Problems cover material from Chapters 18 HW set 6 due on October 17 (Chapter 19) Prof. Kumar tea and cookies.
A new Ad Hoc Positioning System 컴퓨터 공학과 오영준.
ADCS Review – Attitude Determination Prof. Der-Ming Ma, Ph.D. Dept. of Aerospace Engineering Tamkang University.
Dr. Sudharman K. Jayaweera and Amila Kariyapperuma ECE Department University of New Mexico Ankur Sharma Department of ECE Indian Institute of Technology,
9 rad/s2 7 rad/s2 13 rad/s2 14 rad/s2 16 rad/s2
Newton’s 2nd Law: Translational Motion
Chapter 5 Circular Motion. MFMcGraw-PHY 1401Ch5b-Circular Motion-Revised 6/21/ Circular Motion Uniform Circular Motion Radial Acceleration Banked.
Torque on a Current Loop
Lecture 7 – Gravity and Related Issues GISC February 2008.
Fast SLAM Simultaneous Localization And Mapping using Particle Filter A geometric approach (as opposed to discretization approach)‏ Subhrajit Bhattacharya.
Introduction: The on-board measurements available for control are a dual-slit sensor to find the elevation of the sun and a magnetometer to measure the.
STAR SVT Self Alignment V. Perevoztchikov Brookhaven National Laboratory,USA.
Chapter 7 Rotational Motion and The Law of Gravity.
TRIO-CINEMA 1 UCB, 2/08/2010 ACS Dave Auslander, Dave Pankow, Han Chen, Yao-Ting Mao, UC Berkeley Space Sciences Laboratory University of California, Berkeley.
Binding & Dynamic Linking Presented by: Raunak Sulekh(1013) Pooja Kapoor(1008)
From: Nonlinear Dynamical Analysis of the “Power Ball”
Chapter 10 - Rotational Kinematics
Character Animation Forward and Inverse Kinematics
Chapter 8: Rotational Equilibrium and Rotational Dynamics
Aerodynamic Attitude Control for CubeSats
Digital readout architecture for Velopix
ACS UC Berkeley Space Sciences Laboratory
9/16/2018 Physics 253.
Ashray Solanki, Antony Pollail, Lovlish Gupta Undergraduate Students,
Kletskous Magnetic Stabilization
Attitude Determination and Control Preliminary Design Review
RocketSat VII Construction of an Attitude Determination System for a Sounding Rocket COSGC Symposium April 9, 2011.
Attitude Determination Overview
PHYS 1444 – Section 003 Lecture #16
Rigid Body: Rotational and Translational Motion; Rolling without Slipping 8.01 W11D1 Today’s Reading Assignment Young and Freedman: 10.3.
Presentation transcript:

x y z Body frame Goal vector y x y Body frame Goal vector x z Body frame Goal vector x Body frame

Sun normal: Spin mode (assume omega x= omega y=0) omega x, omega y =\=0 If we want to eliminate them, we need to estimate them. Rad/sec 4 rpm Sun elevation near 90 degree (random)

Elevation=0 (not ecliptic normal) Sun normal: precession mode (assume omega x= omega y=0) Not good for initial conditions with high elevation

The sun ECI vector Ecliptic plane

High elevation The sun ECI vector

One strategy: only using one side controller (elevation >0 or elevation <0) elevation Open controller

Omega change Because we only use one coil in z axis, the effects to the spin rate are small 4 rpm omega x, omega y

Conclusion: 1 The storage of battery for the ACS is ok (0.7 w for each “turn on” operation ) 2 test other initial conditions for sun normal mode Issue: 1 need to figure out what happen in the high elevation 2 PIC operation temperature -40 o C~ 85 o C 3 If there are two fixed vectors in the ECI frame, is it possible to know the angular velocities of the three dimension (without any information from the ground )? B field sun B field sun In the view of the body t1t A hour at 8 volt

x y z Body frame Goal vector y x y Body frame Goal vector x z Body frame Goal vector x Body frame

based on the same fixed vector in ECI x z Body frame Goal vector x Body frame x z Y ECI frame Goal vector is fixed If there exists omega x or omega y, the goal vector is no longer fixed in the ECI frame

Time frame =0.01Time frame =0.1 Solver problem Time frame =0.01

Different model structure may produce the errors ! Give the Sun ECI initial condition Give the initial attitude Elevation of the sun in the body frame Due to omega x,omega y Give the Sun ECI initial condition

ground Revolute around local x Revolute around local y Revolute around local z Equator plane Mass: 10e-9 kg Moment of inertia: 10e-7 kgm^2

ground Revolute around local x,y,z And allow slide in x,y,z direction ECI Equator plane

detumble Sun normal :spin up Sun normal: precession Omega x,y,z4 rpm Elevation=0

Precession Sun normal precession elevation Deviation of the attitude (ecliptic normal) Sun normal precession

Average: 27 mins

Z x y bx by bz Rotation matrix: Y(90 degree)  Z(180 degree) Assume: local b field not change much

simulation Local b field ECEF  local b field body frame  local magnetometer frame ACS module rotation matrix and normalized module In PIC

Power from each solar panel (total six panels) 1: with 10 degree constraints for each panel 2: the energy is proportional to the area 3: 15% efficiency for each panel 4: also including the power from the albedo 5 assume in each panel, the power is uniform 6 the area of the solar panel, right now: (10x10 cm) meter square 7 assume the storage: 3.75 A hour at 8 volt= =10 o Z+ X+ Y+ elevation Z- Y- X-

“for the (-X) side, the magnetic dipole moment is estimated to be 0.87 Am 2 consuming 6.43 Watts and drawing 0.80 Amperes. The projected values for the (-Z) side [which has not been built yet] are 0.85 Am2 for the magnetic dipole, 8.63 Watts for power and 1.08 Amperes for current.” Assume 10 duty cycle Sun+albedo Coil zCoil x Results: J for every 0.1 second Error attitude

Max PIC energy consumption W=250 mA*4.0V=1W

1: W=(125-(-40))/40=4.125w maximum allowed power Dissipation or the chip will melt away. 2: W=(100-80)/40=0.5w <1w ?

Indirect access values: With pointers assigning specific address Receive from Rs232, don’t care which memory the compiler assigned … Transmit through Rs232

Data from RS232 Store in the specific memory HSK read values from the specific memory ACS reads values from the specific memory other work ACS store values to the specific memory HSK read values from the specific memory other work Data to RS232 (Torque command) In the future, replaced by other modules, like sun sensor module, MAG module, etc. Just write to the same memory write to the specific memory In the future, replaced by toque command module Int main (){ } Fixed, no change

PIC simulink Another issue: 1:0.7 =real time: simulink

Indirect access values: With pointers assigning specific address Receive from Rs232, don’t care which memory the compiler assigned … Transmit through Rs232

Protocol design and tasks ….. Serial data Begin byte Data set data1data Each variable (total 17) is float, each float includes 4 bytes (17x4=68) Begin byte ….. 1 separate each variable (float->byte) 2 transmit them in the serial port of Simulink 3 receive them in the serial buffer of PIC 4 combine them in the PIC (byte-float)

Structure for parallel testing (run PIC and simulink at the same time, at the same simulink file) Space Environment, Sensor, CINEMA Serial encode Simulink serial interface Serial decode ACS in PIC (c code) ACS in simulink(c code) Serial encode Serial decode Serial encode Serial decode Coil status Simulink serial interface Guarantee all the initial conditions are the same torque Guarantee, the time of switching mode are the same

simulinkPIC Experiment results for the controller (new version)

Power from each solar panel (total six panels) 1: with 10 degree constraints for each panel 2: the energy is proportional to the area 3: 15% efficiency for each panel 4: also including the power from the albedo 5 assume in each panel, the power is uniform 6 the area of the solar panel, right now: (10x10 cm) meter square (x+-:3, y+-:1, z+-:1) 7 assume the storage: 3.75 A hour at 8 volt= =10 o Z+ X+ Y+ elevation Z- Y- X-

The day is longer than the night Accumulating energy

Z+ X+ Y+ elevation Ecliptic normal

Magnetometer sample time: 2 Hz extrapolation Norm of the error in 3 direction

2 Hz

Magnetometer sample time: 5 Hz extrapolation Norm of the error in 3 direction

10Hz 5 Hz

Detumble Detumble+ spin up 2Hz sample time Raw edge

Model Predictive Control MPC slides from Prof. Francesco Borrelli

Do control only for s>0(spin) s>0 s<0 (spin) Least square Using one coil

MPC—using the information of the future and current B field Least square—using the current B field with two coils and various duty cycle Solution sets One coil with fixed duty cycle Two coils with fixed duty cycle

Example--- Get the maximum profits from the Banks in 2 years Need the transfer fee from one bank to the other. The interest rates also depend the total saving in each account One coil: BOA, only allowed to put the all of the money in or out Two coils: Citi, BOA, only allowed to put all of the money in one account Least square: : Citi, BOA, allowed to adjust the money in each account. MPC: Citi, BOA allowed to adjust the money in each account and know the interest rates in the future. This method can also consider other situations.

Linearized the nonlinear systems  continuous model continuous model  discrete model Set the system structure and parameters for the solver Set the translate target set Solver produce the control command Update the current state and insert to the nonlinear system k=k+1 N=N+1

Can update B field for each k

Discrete Model

Final target set Nonlinear system Initial state Translate target set wz wx wy N=1 N=2 N=3 N=0 K=1 K=2

Results: polytope for the feasible region The geometry will update for each k

Detumble mode

Advantage: easy to implement for off-line computation, very flexible and guaranteed optimization in some local region. If the system has no complexity, the optimization no longer exists. Disadvantage: Not good implementation for PIC, it needs more power for the computation for each iteration. Next Step: set the environment of parameters of MPC near the real environment. Investigate the hybrid system. Build the spin up and precession modes in MPC Objection function: consider which variables we want to weight, power, settling time, final step, etc. Control Strategy: Design any controller or adjust parameters in the current controller in the PIC and try to make the results near the results from MPC

Controller 5 Hz: with two coils controller Spin rateattitude

Controller :5 Hz with one coils controller Average: precession over 100 mins

Controller :2 Hz with one coils controller

Sun position 2 HZSun position 5 HZ

MAG data 2 HZ MAG data 5 HZ

Way to eliminate the effects of the albedo Method 1 shadow 1.Measure the minimum power (only from the sun) 2.Get the position of the sun 3.Know the dynamics of the satellite, torque command 4.compute the position of the sun in the future 5.Do Precession, until in the FOV of the sun sensor Disadvantage: hard to keep the initial attitude fixed

Way to eliminate the effects of the albedo Method 2 shadow 1.Set the minimum power band (only from the sun) 2.Get the position of the sun 3.Know the dynamics of the satellite, torque command 4.compute the position of the sun in the future 5.Precession, until in the FOV of the sun sensor advantage: no need to keep the initial attitude fixed

Before switch to the estimator

Rotation matrix Error of Normal 1 of the rotation matrix will disconvenge

Random rotation abound the orbit

42degree, 5 degree 42 o 5o5o

Sun: unit vector Albedo power in x+ Albedo power in x- Albedo power in y+ Albedo power in y- Albedo power in z+ Albedo power in z- Solar Panel module in the simulink Albedo power vector Controller + normalize

X,Y Z+ Z- precession

Extreme case

X,Y Z+ Z- precession

Z+ X,Y 4 rpm Z-

Sun: unit vector Albedo power in x+ Albedo power in x- Albedo power in y+ Albedo power in y- Albedo power in z+ Albedo power in z- Solar Panel module in the simulink Albedo power vector Controller + normalize

Sun: unit vector Albedo power in x+ Albedo power in x- Albedo power in y+ Albedo power in y- Albedo power in z+ Albedo power in z- Controller + normalize separate Solar Panel module in the simulink Convert to a vector

Fix the code for in the controller

Sun: unit vector Albedo power in x+ Albedo power in x- Albedo power in y+ Albedo power in y- Albedo power in z+ Albedo power in z- Controller + normalize separate Solar Panel module in the simulink Convert to a vector Arbitrary disturbance disturbance

Without albedo Without un-viewable angle

Only use Mag data in the spin up B field Body frame: omega=[ ] B field Body frame: omega=[ ] B field Body frame: omega=[ ]

Only use Magnetometer in the spin up B field Body frame: omega=[ ]B field Body frame: omega=[ ] B field Body frame: omega=[ ] B field Body frame: omega=[0 0 0 ]

B field Body frame: omega=[ ] B field Body frame: omega=[ ]

Global weather satellite: rotating Earth rotating Earth with animated clouds covering the most recent 3 week showing current clouds

Conclusion: 1 need to fix the dynamics equation for the sun estimator or compensate it with MAG data—(maybe not necessary) 2 Build the global weather dynamic cloud model in the simulink 3 investigate the determination for the sun position with the info of the geometry of the CINEMA at one instant.

Spin mode without any information from the ground. inititally,w1,w2,w3=0

Assume we can get correct omega z Initial omega x,y,z=[ ]Initial omega x,y,z=[0 0 0]

How to get omega(Wiki) I modify the above as Skew matrix Not invertible  Infinity solutions for omega

R(t)R(t-1) (R(t)-R(t-dt)) W=V/R=(R(t)-R(t-dt))/(dt*R(t)) dt  0 The problem is R not perpendicular with w, we need to separate the vector to horizontal and vertical direction. However, we don’t know the direction of w R(t) w R’ R’’

The above skew matrix (n=3) is rank 2 combine the information with solar panels to make it becomes rank 3 Algorithm omega estimator by Y.T Mao

Simulation results Omega xOmega y Omega z Initial Omega=[ ]

Denominator vs omega x

A approach to fix it Consider the all the combination from B field and Sun position (body frame) Results for combination: b field, sun (1,2)(1) (1,2)(2) (1,2)(3) Omega x Omega y Omega z Chose the biggest determinant

Include with solar panel module (assume Mag is prefect) Omega x Omega y Omega z

Do spin up with the estimate omega (without any information from the ground station) Estimate omega x Estimate omegay Estimate omega z

With static albedo(ice) Error angle between the real sun and the effected sun Albedo power in the x +plame

Conclusion: 1 It is ok to use the solar panels and Mag to do spin up without ground station. 2 Try to only use historical data of Mag for the next task. 3 incorporate new omega estimation module in the ACS module of the PIC. 4 investigate the determination for the sun position with the info of the geometry of the CINEMA at one instant. 5 try to use only B field (ground), B field(body), sun position(body) to do the attitude determination(without sun position(ground) estimator, need the exactly launch time)

Detumble Detumble+ spin up 2Hz sample time Raw edge

R(t)R(t-1) (R(t)-R(t-dt)) W=V/R=(R(t)-R(t-dt))/(dt*R(t)) dt  0 The problem is R not perpendicular with w, we need to separate the vector to horizontal and vertical direction. However, we don’t know the direction of w R(t) w R’ R’’