示例#1
0
文件: MHE.py 项目: ghorn/rawesome
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)
示例#2
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文件: MHE.py 项目: psinha/rawesome
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)
示例#3
0
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++')