def makeMhe(dae,N,dt):
from rawe.ocp import Ocp
mhe = Ocp(dae, N=N, ts=dt)
ocpOpts = rawe.OcpExportOptions()
ocpOpts['HESSIAN_APPROXIMATION'] = 'GAUSS_NEWTON'
ocpOpts['DISCRETIZATION_TYPE'] = 'MULTIPLE_SHOOTING'
ocpOpts['QP_SOLVER'] = 'QP_QPOASES'
ocpOpts['HOTSTART_QP'] = False
ocpOpts['SPARSE_QP_SOLUTION'] = 'CONDENSING'
# ocpOpts['SPARSE_QP_SOLUTION'] = 'FULL_CONDENSING_U2'
# ocpOpts['AX_NUM_QP_ITERATIONS'] = '30'
ocpOpts['FIX_INITIAL_STATE'] = False
# mhe.minimizeLsq(C.veccat([mhe['x'],mhe['u']]))
# mhe.minimizeLsqEndTerm(C.veccat([mhe['x']]))
mhe.minimizeLsq(mhe['measurements'])
mhe.minimizeLsqEndTerm(mhe['measurementsN'])
cgOpts = {'CXX':'g++', 'CC':'gcc'}
print "makeMhe calling rawe.OcpRT"
return rawe.OcpRT(mhe, ocpOptions=ocpOpts, integratorOptions=intOpts,
codegenOptions=cgOpts)
def makeMhe(dae,N,dt):
from rawe.ocp import Ocp
mhe = Ocp(dae, N=N, ts=dt)
ocpOpts = rawe.OcpExportOptions()
ocpOpts['HESSIAN_APPROXIMATION'] = 'GAUSS_NEWTON'
ocpOpts['DISCRETIZATION_TYPE'] = 'MULTIPLE_SHOOTING'
ocpOpts['QP_SOLVER'] = 'QP_QPOASES'
ocpOpts['HOTSTART_QP'] = False
ocpOpts['SPARSE_QP_SOLUTION'] = 'CONDENSING'
# ocpOpts['SPARSE_QP_SOLUTION'] = 'FULL_CONDENSING_U2'
# ocpOpts['AX_NUM_QP_ITERATIONS'] = '30'
ocpOpts['FIX_INITIAL_STATE'] = False
# mhe.minimizeLsq(C.veccat([mhe['x'],mhe['u']]))
# mhe.minimizeLsqEndTerm(C.veccat([mhe['x']]))
mhe.minimizeLsq(mhe['measurements'])
mhe.minimizeLsqEndTerm(mhe['measurementsN'])
cgOpts = {'CXX':'g++', 'CC':'gcc'}
print "makeMhe calling rawe.OcpRT"
return rawe.OcpRT(mhe, ocpOptions=ocpOpts, integratorOptions=intOpts,
codegenOptions=cgOpts)
import casadi as C
if __name__=='__main__':
dae = rawe.dae.Dae()
[pos,vel] = dae.addX( ["pos","vel"] )
dae.addZ('dummyZ')
force = dae.addU( "force" )
endTime = dae.addP( 'someRandomParameter' )
# specify the dae residual
dae.setResidual([dae.ddt('pos') - vel,
dae.ddt('vel') - (force - 3.0*pos - 0.2*vel),
dae['dummyZ']])
from rawe.ocp import Ocp
mpc = Ocp(dae, N=10, ts=0.2)
mpc.constrain(mpc['pos'], '==', 3, when='AT_START')
mpc.constrain(mpc['vel'], '==', 0, when='AT_START')
mpc.constrain(mpc['pos'], '==', 0, when='AT_END')
mpc.constrain(mpc['vel'], '==', 0, when='AT_END')
mpc.constrain(mpc['force']**2, '<=', 4)
mpc.constrain(mpc['someRandomParameter']/4.0, '<=', 2)
mpc.minimizeLsq(C.veccat([mpc['pos'],mpc['vel'],mpc['someRandomParameter']]))
mpc.minimizeLsqEndTerm(C.veccat([mpc['pos']]))
mpc.exportCode(CXX='clang++')
