A Miniaturized Satellite Attitude Determination and Control System with Autonomous Calibration Capabilities

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A Miniaturized Satellite Attitude Determination and Control System with Autonomous Calibration Capabilities Sanny Omar Dr. David Beale Dr. JM Wersinger

Introduction ADACS designed for CubeSats CubeSats generally range in size from 1U to 3U (10x10x(10-30) cm) Relatively cheap and easy to build Highly capable due to miniaturized technology Require attitude control systems to properly orient science instruments and antennas

Sensors and Actuators Trade Study 10 is most desirable, 1 is least desirable Name Cost Complexity Legacy Accuracy Totals Magnetometer 8 8 10 6 32 Horizon Sensor 6 7 8 8 29 Sun Sensor 10 9 10 2 31 Star Tracker 1 3 5 10 19 Rate Gyros 10 8 8 5 31 Magnetorquers 10 6 10 5 31 3-axis Reaction Wheels 7 6 8 9 30 Gravity Boom 10 10 1 2 23 Aerodynamic Stabilization 10 10 2 5 27

Sensors and Actuators Reaction Wheels (3) Magnetorquers (3) Magnetometer (3-axis) Rate gyros (3-axis) Position Sensitive Detectors (PSDs)

Coordinate Frames Earth Fixed Inertial Frame Origin at Earth center, x- axis toward vernal equinox, z-axis through North Pole Orbital Frame Origin at satellite cm, x-axis aligned with velocity, z-axis toward Earth Satellite Body Frame Origin at satellite cm and moves with the satellite

Coordinate Frame Transformation rx2 a11 a12 a13 rx1 r = a a a r y2 21 22 23 y1 r z2 a31 a32 a 33 r z1 q q 0 1 x = q q 2 3 cos( θ ) 2 n sin( θ ) 2 ny sin( θ ) 2 nz sin( θ ) 2

Attitude Vectors Sun vector in body frame from PSDs Magnetic field vector in body frame from magnetometer Magnetic field vector in orbital frame from IGRF model Sun vector in orbital frame from heliocentric orbit propagator Angular velocity vector (in body frame) from rate gyros

Attitude Determination Defined as direction cosine matrix between body frame and orbital frame Triad algorithm gives DCM based on two vectors known in both frames R1 R2 R1 R 2 = [ A] r1 r2 r1 r2 DCM to quaternion conversion ( ) ( ) q tr( A) + 1 a + a + a + 1 = = 4 4 a32 a23 q1 = 4q0 a13 a31 q2 = 4q0 a21 a12 q3 = 4q 2 11 22 33 0 0

Error Quaternion Relates current orientation to desired orientation Used in control algorithm Calculated based on measured and desired quaternions (q m and q d ) q0 q1 q2 q3 d d d d q1 q d 0 q d 3 q d 2d Ld = q2 q d 3 q d 0 q d 1d q3 q d 2 q d 1 q d 0d q = Lq e d m

Control Algorithm T (s) = s 2 k p k p skd + 2

Inverse Dynamics PD Controller Takes satellite dynamics into account Ensures stability in all conditions PD law determines desired angular accelerations Equations of motion used to calculate required torques Gains independent of inertia properties αx qe1 ωx α = k q + k ω y p e2 d y α z q e3 ω z M dh = = 0 dt Tx α1 I11 0 0 ωx ω1 ωx Ixx 0 0 αx T y I w α 2 0 I22 0 ω y I w ω 2 ω y 0 Iyy 0 α = = + y T α 0 0 I ω ω ω 0 0 I α z m 3 w 33 sc z sc 3 w z sc zz sc z sc

Drawbacks of Direct Linear PD Controller Torques calculated directly from controller Tx kpxq e1 kdxωx T y kpyq e2 kdyω = + y T z k m pzq e3 kdzω z Controller does not take wheel angular momentum into account Can result in instability Controller gains dependent on satellite inertia properties Separate gain value needed for each parameter

Instability of Direct PD Control when Angular Momentum is Large

Inverse Dynamics PD Controller Performance Desired angular accelerations achieved perfectly Performance independent of initial conditions and system inertia properties System exhibits a stable oscillatory equilibrium Frequency and amplitude of oscillations decreases as system becomes more overdamped Adding integral term does not mitigate oscillations More work needed to determine exact cause for oscillations

Underdamped Case (K p =1, k d =-.5) Critically Damped Case (K p =1, k d =-1.4) Overdamped Case (K p =1, k d =-4)

Simulations with Kp = 1 and Kd = -4

K p = 1 k d = -8 K p = 1 k d = -20

Minimizing Oscillations

Simulations with K p = 200

Active Momentum Dumping Magnetorquers constantly work to reduce wheel angular momentum (H w ) ω1 Hw = I w ω 2 ω 3 µ id = k* H w B ( ) ( ) T = µ id B = k* H w B B

Autonomous In-Flight Calibration Estimate moments of inertia and angular velocity based on kinematic response Calibrate to correct bias error in rate gyros. ω ω ω x z y = = = M dh dt = + ω sc I α = I α s s w w I ωω I ω I ωz w y 1 w 3 zz ( ) I I ω + I ω yy xx y w 3 I ωω + I ω I ωy w x 3 w 2 yy ( ) I I ω + I xx zz x w w z 2 w 1 xx ( ) zz yy z w H ω 1 x I ωω I ω I ω I I ω + I ω 3

Estimated Cost Four Positions Sensitive Detectors - $1000 total Three Magnetorquers - $100 total Three Reaction Wheels - $300 total Electronic Speed Controller - $50 Magnetometer - $100 Rate gyros - $100 Microcontroller and PCB - $200 Total - $1850

Questions? Contact: Sanny Omar AubieSat Team sanny.omar@gmail.com