#
# ISC License
#
# Copyright (c) 2016, Autonomous Vehicle Systems Lab, University of Colorado at Boulder
#
# Permission to use, copy, modify, and/or distribute this software for any
# purpose with or without fee is hereby granted, provided that the above
# copyright notice and this permission notice appear in all copies.
#
# THE SOFTWARE IS PROVIDED "AS IS" AND THE AUTHOR DISCLAIMS ALL WARRANTIES
# WITH REGARD TO THIS SOFTWARE INCLUDING ALL IMPLIED WARRANTIES OF
# MERCHANTABILITY AND FITNESS. IN NO EVENT SHALL THE AUTHOR BE LIABLE FOR
# ANY SPECIAL, DIRECT, INDIRECT, OR CONSEQUENTIAL DAMAGES OR ANY DAMAGES
# WHATSOEVER RESULTING FROM LOSS OF USE, DATA OR PROFITS, WHETHER IN AN
# ACTION OF CONTRACT, NEGLIGENCE OR OTHER TORTIOUS ACTION, ARISING OUT OF
# OR IN CONNECTION WITH THE USE OR PERFORMANCE OF THIS SOFTWARE.
#
import matplotlib.pyplot as plt
import numpy as np
import pytest
from Basilisk.architecture import messaging
from Basilisk.fswAlgorithms import mrpSteering # import the module that is to be tested
from Basilisk.fswAlgorithms import rateServoFullNonlinear
from Basilisk.utilities import RigidBodyKinematics
from Basilisk.utilities import SimulationBaseClass
from Basilisk.utilities import macros
from Basilisk.utilities import unitTestSupport # general support file with common unit test functions
# uncomment this line is this test is to be skipped in the global unit test run, adjust message as needed
# @pytest.mark.skipif(conditionstring)
# uncomment this line if this test has an expected failure, adjust message as needed
# @pytest.mark.xfail() # need to update how the RW states are defined
# provide a unique test method name, starting with test_
[docs]@pytest.mark.parametrize("K1", [0.15, 0])
@pytest.mark.parametrize("K3", [1, 0])
@pytest.mark.parametrize("omegaMax", [1.5 * macros.D2R, 0.001])
def test_mrp_steering_tracking(show_plots,K1, K3, omegaMax):
r"""
**Validation Test Description**
This unit test is an integrated test of this module with :ref:`rateServoFullNonlinear` as well,
comparing the desired torques computed :math:`{\bf L}_r` with truth values computed in the test.
**Test Parameters**
This test checks a set of gains ``K1``, ``K3`` and ``omegaMax`` on a rigid body with no external
torques, and with a fixed input reference attitude message. The commanded rate solution
is evaluated against python computed values at 0s, 0.5s, 1.0s, 1.5s and 2s to within a
tolerance of :math:`10^{-12}`.
:param show_plots: flag indicating if plots should be shown.
:param K1: The control gain :math:`K_1`
:param K3: The control gain :math:`K_3`
:param omegaMax: The control gain :math:`\omega_{\text{max}}`
:return: void
"""
[testResults, testMessage] = mrp_steering_tracking(show_plots,K1, K3, omegaMax)
assert testResults < 1, testMessage
def mrp_steering_tracking(show_plots,K1, K3, omegaMax):
# The __tracebackhide__ setting influences pytest showing of tracebacks:
# the mrp_steering_tracking() function will not be shown unless the
# --fulltrace command line option is specified.
__tracebackhide__ = True
testFailCount = 0 # zero unit test result counter
testMessages = [] # create empty list to store test log messages
unitTaskName = "unitTask" # arbitrary name (don't change)
unitProcessName = "TestProcess" # arbitrary name (don't change)
# Create a sim module as an empty container
unitTestSim = SimulationBaseClass.SimBaseClass()
# Create test thread
testProcessRate = macros.sec2nano(0.5) # update process rate update time
testProc = unitTestSim.CreateNewProcess(unitProcessName)
testProc.addTask(unitTestSim.CreateNewTask(unitTaskName, testProcessRate))
# Construct algorithm and associated C++ container
module = mrpSteering.mrpSteering()
module.ModelTag = "mrpSteering"
servo = rateServoFullNonlinear.rateServoFullNonlinear()
servo.ModelTag = "rate_servo"
# Add test module to runtime call list
unitTestSim.AddModelToTask(unitTaskName, module)
unitTestSim.AddModelToTask(unitTaskName, servo)
module.K1 = K1
module.K3 = K3
module.omega_max = omegaMax
servo.Ki = 0.01
servo.P = 150.0
servo.integralLimit = 2. / servo.Ki * 0.1
servo.knownTorquePntB_B = [0., 0., 0.]
# Create input message and size it because the regular creator of that message
# is not part of the test.
# attGuidOut Message:
guidCmdData = messaging.AttGuidMsgPayload() # Create a structure for the input message
guidCmdData.sigma_BR = [0.3, -0.5, 0.7]
guidCmdData.omega_BR_B = [0.010, -0.020, 0.015]
guidCmdData.omega_RN_B = [-0.02, -0.01, 0.005]
guidCmdData.domega_RN_B = [0.0002, 0.0003, 0.0001]
guidInMsg = messaging.AttGuidMsg().write(guidCmdData)
# vehicleConfigData Message:
vehicleConfigOut = messaging.VehicleConfigMsgPayload()
I = [1000., 0., 0.,
0., 800., 0.,
0., 0., 800.]
vehicleConfigOut.ISCPntB_B = I
vcInMsg = messaging.VehicleConfigMsg().write(vehicleConfigOut)
# wheelSpeeds Message
rwSpeedMessage = messaging.RWSpeedMsgPayload()
Omega = [10.0, 25.0, 50.0, 100.0]
rwSpeedMessage.wheelSpeeds = Omega
rwInMsg = messaging.RWSpeedMsg().write(rwSpeedMessage)
# wheelConfigData message
def writeMsgInWheelConfiguration():
rwConfigParams = messaging.RWArrayConfigMsgPayload()
rwConfigParams.GsMatrix_B = [
1.0, 0.0, 0.0,
0.0, 1.0, 0.0,
0.0, 0.0, 1.0,
0.5773502691896258, 0.5773502691896258, 0.5773502691896258
]
rwConfigParams.JsList = [0.1, 0.1, 0.1, 0.1]
rwConfigParams.numRW = 4
msg = messaging.RWArrayConfigMsg().write(rwConfigParams)
jsList = rwConfigParams.JsList
GsMatrix_B = rwConfigParams.GsMatrix_B
return jsList, GsMatrix_B, msg
jsList, GsMatrix_B, rwParamInMsg = writeMsgInWheelConfiguration()
# wheelAvailability message
rwAvailList = []
rwAvailabilityMessage = messaging.RWAvailabilityMsgPayload()
rwAvail = [messaging.AVAILABLE, messaging.AVAILABLE, messaging.AVAILABLE, messaging.AVAILABLE]
rwAvailabilityMessage.wheelAvailability = rwAvail
rwAvailInMsg = messaging.RWAvailabilityMsg().write(rwAvailabilityMessage)
rwAvailList.append(rwAvail)
# Setup logging on the test module output message so that we get all the writes to it
dataLog = servo.cmdTorqueOutMsg.recorder()
unitTestSim.AddModelToTask(unitTaskName, dataLog)
# connect messages
module.guidInMsg.subscribeTo(guidInMsg)
servo.guidInMsg.subscribeTo(guidInMsg)
servo.vehConfigInMsg.subscribeTo(vcInMsg)
servo.rwParamsInMsg.subscribeTo(rwParamInMsg)
servo.vehConfigInMsg.subscribeTo(vcInMsg)
servo.rwSpeedsInMsg.subscribeTo(rwInMsg)
servo.rateSteeringInMsg.subscribeTo(module.rateCmdOutMsg)
servo.rwAvailInMsg.subscribeTo(rwAvailInMsg)
# Need to call the self-init and cross-init methods
unitTestSim.InitializeSimulation()
# Step the simulation to 3*process rate so 4 total steps including zero
unitTestSim.ConfigureStopTime(macros.sec2nano(1.0)) # seconds to stop simulation
unitTestSim.ExecuteSimulation()
servo.Reset(1) # this module reset function needs a time input (in NanoSeconds)
unitTestSim.ConfigureStopTime(macros.sec2nano(2.0)) # seconds to stop simulation
unitTestSim.ExecuteSimulation()
# Compute true values
trueVals = findTrueTorques(module, servo, guidCmdData, rwSpeedMessage, vehicleConfigOut, rwAvailList)
# set the filtered output truth states
# compare the module results to the truth values
accuracy = 1e-12
for i in range(0, len(trueVals)):
# check a vector values
if not unitTestSupport.isArrayEqual(dataLog.torqueRequestBody[i], trueVals[i], 3, accuracy):
testFailCount += 1
testMessages.append("FAILED: " + module.ModelTag + " Module failed torqueRequestBody unit test at t="
+ str(dataLog.times[i] * macros.NANO2SEC) + "sec \n")
# If the argument provided at commandline "--show_plots" evaluates as true,
# plot all figures
if show_plots:
plt.show()
# print out success message if no error were found
if testFailCount == 0:
print("PASSED: " + module.ModelTag)
# return fail count and join into a single string all messages in the list
# testMessage
return [testFailCount, ''.join(testMessages)]
def findTrueValues(guidCmdData, module):
omegaMax = module.omega_max
sigma = np.asarray(guidCmdData.sigma_BR)
K1 = np.asarray(module.K1)
K3 = np.asarray(module.K3)
Bmat = RigidBodyKinematics.BmatMRP(sigma)
omegaAst = []#np.asarray([0, 0, 0])
omegaAst_P = []
for i in range(len(sigma)):
steerRate = -1*(2*omegaMax/np.pi)*np.arctan((K1*sigma[i]+K3*sigma[i]*sigma[i]*sigma[i])*np.pi/(2*omegaMax))
omegaAst.append(steerRate)
#print omegaAst
if 1:#module.ignoreOuterLoopFeedforward: #should be "if not"
sigmaP = 0.25*Bmat.dot(omegaAst)
for i in range(len(sigma)):
omegaAstRate = (K1+3*K3*sigma[i]**2)/(1+((K1*sigma[i]+K3*sigma[i]**3)**2)*(np.pi/(2*omegaMax))**2)*sigmaP[i]
omegaAst_P.append(-omegaAstRate)
else:
omegaAst_P = np.asarray([0, 0, 0])
return omegaAst, omegaAst_P
def findTrueTorques(module,servo, guidCmdData,rwSpeedMessage,vehicleConfigOut, rwAvailMsg):
Lr = []
#Read in variables
numRW = servo.rwConfigParams.numRW
L = np.asarray(servo.knownTorquePntB_B)
steps = [0, 0, .5, 0, .5]
omega_BR_B = np.asarray(guidCmdData.omega_BR_B)
omega_RN_B = np.asarray(guidCmdData.omega_RN_B)
omega_BN_B = omega_BR_B + omega_RN_B #find body rate
domega_RN_B = np.asarray(guidCmdData.domega_RN_B)
omega_BastR_B, omegap_BastR_B = findTrueValues(guidCmdData, module)
omega_BastN_B = omega_BastR_B+omega_RN_B
omega_BBast_B = omega_BN_B - omega_BastN_B
Isc = np.asarray(vehicleConfigOut.ISCPntB_B)
Isc = np.reshape(Isc, (3, 3))
Ki = servo.Ki
P = servo.P
jsVec = servo.rwConfigParams.JsList[0:numRW]
#GsMatrix_B_array = np.asarray(GsMatrix)
GsMatrix = (servo.rwConfigParams.GsMatrix_B)
GsMatrix_B_array = np.reshape(GsMatrix[0:numRW * 3], (numRW, 3))
#Compute toruqes
for i in range(len(steps)):
dt = steps[i]
if dt == 0:
zVec = np.asarray([0, 0, 0])
#evaluate integral term
if Ki > 0 and abs(servo.integralLimit) > 0: #if integral feedback is on
zVec = dt * omega_BBast_B + zVec # z = integral(del_omega)
# Make sure each component is less than the integral limit
for i in range(3):
if zVec[i] > servo.integralLimit:
zVec[i] = zVec[i]/abs(zVec[i])*servo.integralLimit
else: #integral gain turned off/negative setting
zVec = np.asarray([0, 0, 0])
#compute torque Lr
Lr0 = Ki * zVec # +K*sigmaBR
Lr1 = Lr0 + P * omega_BBast_B # +P*deltaOmega
GsHs = np.array([0,0,0])
if numRW > 0:
for i in range(numRW):
if rwAvailMsg[0][i] == 0: # Make RW availability check
GsHs = GsHs + np.dot(GsMatrix_B_array[i, :], jsVec[i]*(np.dot(omega_BN_B, GsMatrix_B_array[i, :]) + rwSpeedMessage.wheelSpeeds[i]))
# J_s*(dot(omegaBN_B,Gs_vec)+Omega_wheel)
Lr2 = Lr1 - np.cross(omega_BastN_B, (Isc.dot(omega_BN_B)+GsHs)) # - omega_BastN x ([I]omega + [Gs]h_s)
Lr3 = Lr2 - Isc.dot(omegap_BastR_B + domega_RN_B - np.cross(omega_BN_B, omega_RN_B))
# - [I](d(omega_B^ast/R)/dt + d(omega_r)/dt - omega x omega_r)
Lr4 = Lr3 + L
Lr4 = -Lr4
Lr.append(np.ndarray.tolist(Lr4))
return Lr
if __name__ == "__main__":
test_mrp_steering_tracking(False, 0.15, 1.0, 0.025)