def get_dp_bc_params(state):
    dp_bc_xy = Matrix(lam_bc_com(state[1], state[2]))
    dp_bc_xy_inertial = Matrix(lam_bc_com_inertial(state[0], state[1], state[2]))
    dp_bc_length = (dp_bc_xy[0]**2 + dp_bc_xy[1]**2)**0.5
    dp_bc_angle = -atan(dp_bc_xy[0]/dp_bc_xy[1]) #angle with respect to angle one
    dp_bc_vel_xy = Matrix(lam_bc_com_dot(state[1], state[2], state[4], state[5]))
    dp_bc_ang_vel = (dp_bc_xy.cross(dp_bc_vel_xy))/norm(dp_bc_xy)**2
    dp_bc_params_dict = dict(zip(['bc_length', 'bc_theta', 'bc_ang_vel', 'bc_loc', 'bc_vel_xy'], [dp_bc_length, dp_bc_angle, dp_bc_ang_vel[2], dp_bc_xy_inertial, dp_bc_vel_xy])) 
    return dp_bc_params_dict
Exemplo n.º 2
0
def get_sp_des_xy_acc(params, state):
    com_vel_xy = Matrix(lam_com_dot_eq(state[0], state[1], state[2], state[3]))
    com_ang_vel = (params.get('sp_com_xy').cross(com_vel_xy))/(norm(params.get('sp_com_xy')))**2
    com_ang_vel = com_ang_vel[2]
    com_u = -k_p*params.get('sp_theta') + -k_v*com_ang_vel
    com_ang_acc = Matrix([0,0,lam_sp_eq_torque_only(params.get('sp_length'), com_u)])
    com_ang_acc = com_ang_acc[2]
    com_ang_acc_xy = Matrix([lam_sp_com_x(params.get('sp_length'), params.get('sp_theta'), com_ang_vel, com_ang_acc), lam_sp_com_y(params.get('sp_length'), params.get('sp_theta'), com_ang_vel, com_ang_acc)])
    com_ang_acc_dict = dict(zip(['ang_acc_x', 'ang_acc_y', 'ang_acc'], [com_ang_acc_xy[0], com_ang_acc_xy[1], com_ang_acc]))
    return com_ang_acc_dict
def get_sp_des_xy_acc(params, state): #returns desired com x and y acceleration based off of PD control of the center of mass pendulum
    global k_p, k_v
    com_vel_xy = Matrix(lam_com_dot_eq(state[0], state[1], state[2], state[3], state[4], state[5]))
    com_ang_vel = (params.get('sp_com_xy').cross(com_vel_xy))/(norm(params.get('sp_com_xy')))**2
    com_ang_vel = com_ang_vel[2]
    com_u = -k_p*params.get('sp_theta') + -k_v*com_ang_vel #pd torque control

#    com_ang_acc = Matrix([0,0, lam_sp_eq(params.get('sp_length'), params.get('sp_theta'), com_u)]) #angular acceleration resulting from pd torque control
    com_ang_acc = Matrix([0,0, lam_sp_eq_torque_only(params.get('sp_length'), com_u)])
    com_ang_acc_xy = (com_ang_acc.cross(params.get('sp_com_xy')))
    com_ang_acc_dict = dict(zip(['ang_acc_x', 'ang_acc_y'], [com_ang_acc_xy[0], com_ang_acc_xy[1]]))
#    com_ang_acc_dict = dict(zip(['ang_acc_x', 'ang_acc_y'], [com_ang_acc_xy[0], 0.0]))
    return com_ang_acc_dict
Exemplo n.º 4
0
Arquivo: mpmat.py Projeto: bayao/qml
def test_mev():
    output("""\
    reim:{$[0>type x;1 0*x;2=count x;x;'`]};
    mc:{((x[0]*y 0)-x[1]*y 1;(x[0]*y 1)+x[1]*y 0)};
    mmc:{((.qml.mm[x 0]y 0)-.qml.mm[x 1]y 1;(.qml.mm[x 0]y 1)+.qml.mm[x 1]y 0)};
    mev_:{[b;x]
        if[2<>count wv:.qml.mev x;'`length];
        if[not all over prec>=abs
            mmc[flip vc;flip(flip')(reim'')flip x]-
            flip(w:reim'[wv 0])mc'vc:(flip')(reim'')(v:wv 1);'`check];
        / Normalize sign; LAPACK already normalized to real
        v*:1-2*0>{x a?max a:abs x}each vc[;0];
        (?'[prec>=abs w[;1];w[;0];w];?'[b;v;0n])};""")

    for A in eigenvalue_subjects:
        if A.rows <= 3:
            V = []
            for w, n, r in A.eigenvects():
                w = sp.simplify(sp.expand_complex(w))
                if len(r) == 1:
                    r = r[0]
                    r = sp.simplify(sp.expand_complex(r))
                    r = r.normalized() / sp.sign(max(r, key=abs))
                    r = sp.simplify(sp.expand_complex(r))
                else:
                    r = None
                V.extend([(w, r)]*n)
            V.sort(key=lambda (x, _): (-abs(x), -sp.im(x)))
        else:
            Am = mp.matrix(A)
            # extra precision for complex pairs to be equal in sort
            with mp.extradps(mp.mp.dps):
                W, R = mp.eig(Am)
            V = []
            for w, r in zip(W, (R.column(i) for i in range(R.cols))):
                w = mp.chop(w)
                with mp.extradps(mp.mp.dps):
                    _, S, _ = mp.svd(Am - w*mp.eye(A.rows))
                if sum(x == 0 for x in mp.chop(S)) == 1:
                    # nullity 1, so normalized eigenvector is unique
                    r /= mp.norm(r) * mp.sign(max(r, key=abs))
                    r = mp.chop(r)
                else:
                    r = None
                V.append((w, r))
            V.sort(key=lambda (x, _): (-abs(x), -x.imag))
        W, R = zip(*V)
        test("mev_[%sb" % "".join("0" if r is None else "1" for r in R), A,
             (W, [r if r is None else list(r) for r in R]), complex_pair=True)
def controller(x, t):
    global torque_vector, time_vector, x_vector
    returnval = [0., 0., 0.]
    global_sp_params = get_global_com_params(x) #convert from triple pendulum to single pendulum
    desired_global_sp_acc_xy = get_sp_des_xy_acc(global_sp_params, x) #calculates desired single pendulum acceleration
    dp_bc_params = get_dp_bc_params(x)
    dp_two_params = dict(zip(['length', 'mass', 'angle', 'ang_vel'], 
                             [dp_bc_params.get('bc_length'),
                              parameter_dict.get(tp.b_mass) + parameter_dict.get(tp.c_mass),
                              x[1] + x[2], 
                              dp_bc_params.get('bc_ang_vel')])) #params for link 2 of dp1 model
    dp_one_params = dict(zip(['length', 'mass', 'angle', 'ang_vel'], 
                             [parameter_dict.get(tp.a_length),
                              parameter_dict.get(tp.a_mass), 
                              x[0], 
                              x[3]])) #params for link 1 of dp1 model
    dp_angular = get_dp_angular_from_com_xy_acc(dp_one_params, dp_two_params, desired_global_sp_acc_xy) #yields desired a1 and a2 for dp1 based on desired single pendulum acceleration
    dp_desired_torques = dp_inverse_dynamics(dp_one_params, dp_two_params, dp_angular) #torque_a set to that required to produce desired dp acceleration by inverse dynamics
    returnval[0] = dp_desired_torques.get('one_torque')
    
    dp2_com_ang_acc = (dp_bc_params.get('bc_loc').cross(Matrix([0,0,dp_angular.get('theta2_acc')])))/(norm(dp_bc_params.get('bc_loc'))**2)
    dp2_com_ang_acc = dict(zip(['ang_acc_x', 'ang_acc_y'], [dp2_com_ang_acc[0], dp2_com_ang_acc[1]]))
    dp_one_params = dict(zip(['length', 'mass', 'angle', 'ang_vel'],
                             [parameter_dict.get(tp.b_length),
                              parameter_dict.get(tp.b_mass),
                              x[0] + x[1],
                              x[3] + x[4]]))
    dp_two_params = dict(zip(['length', 'mass', 'angle', 'ang_vel'],
                             [parameter_dict.get(tp.c_length),
                              parameter_dict.get(tp.c_mass),
                              x[2],
                              x[5]]))
                              
    dp_angular = get_dp_angular_from_com_xy_acc(dp_one_params, dp_two_params, dp2_com_ang_acc)
    dp_desired_torques = dp_inverse_dynamics(dp_one_params, dp_two_params, dp_angular)
    returnval[1] = dp_desired_torques.get('one_torque')
    returnval[2] = dp_desired_torques.get('two_torque')
    
    if(returnval[0] > 10.0):
        returnval[0] = 10.0
    if(returnval[0] < -10.0):
        returnval[0] = -10.0
    if(returnval[1] > 10.0):
        returnval[1] = 10.0
    if(returnval[1] < -10.0):
        returnval[1] = -10.0
    if(returnval[2] > 10.0):
        returnval[2] = 10.0
    if(returnval[2] < -10.0):
        returnval[2] = -10.0
    torque_vector.append(returnval)
    time_vector.append(t)
    x_vector.append(x)
    return returnval
def controller(x, t):
    global torque_vector, time_vector, x_vector, com_vector
    x_vector.append(x)
#    print(x)
    returnval = [0., 0., 0.]
    global_sp_params = get_global_com_params(x) #convert from triple pendulum to single pendulum
    com_vector.append(global_sp_params.get('sp_com_xy'))
    desired_global_sp_acc_xy = get_sp_des_xy_acc(global_sp_params, x) #calculates desired single pendulum acceleration
    dp_bc_params = get_dp_bc_params(x)
    dp_two_params = dict(zip(['length', 'com_x', 'com_y', 'com_x_dot', 'com_y_dot', 'mass', 'angle', 'ang_vel'], 
                             [dp_bc_params.get('bc_length'),
                              dp_bc_params.get('bc_loc')[0],
                              dp_bc_params.get('bc_loc')[1],
                              dp_bc_params.get('bc_vel_xy')[0],
                              dp_bc_params.get('bc_vel_xy')[1],
                              parameter_dict.get(tp_b_mass) + parameter_dict.get(tp_c_mass),
                              x[1]+x[2], 
                              dp_bc_params.get('bc_ang_vel')])) #params for link 2 of dp1 model
    com_a = Matrix(lam_a_com(x[0]))
    com_a_dot = Matrix(lam_a_com_dot(x[0], x[3]))
    dp_one_params = dict(zip(['length', 'com_x', 'com_y', 'com_x_dot', 'com_y_dot', 'mass', 'angle', 'ang_vel'], 
                             [parameter_dict.get(tp_a_length),
                              com_a[0],
                              com_a[1],
                              com_a_dot[0],
                              com_a_dot[1],
                              parameter_dict.get(tp_a_mass), 
                              x[0], 
                              x[3]])) #params for link 1 of dp1 model
    rb_angular = get_pp_angular_from_com_xy_acc(dp_one_params, dp_two_params, desired_global_sp_acc_xy) #yields desired a1 and a2 for dp1 based on desired single pendulum acceleration
    des_acc.append([rb_angular.get('theta1_acc'), rb_angular.get('theta2_acc')])
    print([rb_angular.get('theta1_acc'), rb_angular.get('theta2_acc')])
    rb_desired_torques = rb_inverse_dynamics(dp_one_params, dp_two_params, rb_angular) #torque_a set to that required to produce desired dp acceleration by inverse dynamics
    returnval[0] = rb_desired_torques.get('one_torque')
    
    dp2_com_ang_acc = (dp_bc_params.get('bc_loc').cross(Matrix([0,0, rb_angular.get('theta2_acc')])))/(norm(dp_bc_params.get('bc_loc'))**2)
    dp2_com_ang_acc = dict(zip(['ang_acc_x', 'ang_acc_y'], [dp2_com_ang_acc[0], dp2_com_ang_acc[1]]))
    dp_one_params = dict(zip(['length', 'mass', 'angle', 'ang_vel'],
                             [parameter_dict.get(tp_b_length),
                              parameter_dict.get(tp_b_mass),
                              x[0] + x[1],
                              x[4]]))
    dp_two_params = dict(zip(['length', 'mass', 'angle', 'ang_vel'],
                             [parameter_dict.get(tp_c_length),
                              parameter_dict.get(tp_c_mass),
                              x[2],
                              x[5]]))
                              
    pp_angular = get_pp_angular_from_com_xy_acc(dp_one_params, dp_two_params, dp2_com_ang_acc)
    pp_desired_torques = pp_inverse_dynamics(dp_one_params, dp_two_params, pp_angular)
    
    returnval[1] = pp_desired_torques.get('one_torque')
    returnval[2] = pp_desired_torques.get('two_torque')
    
    if(returnval[0] > 20.0):
        returnval[0] = 20.0
    if(returnval[0] < -20.0):
        returnval[0] = -20.0
    if(returnval[1] > 20.0):
        returnval[1] = 20.0
    if(returnval[1] < -20.0):
        returnval[1] = -20.0
    if(returnval[2] > 20.0):
        returnval[2] = 20.0
    if(returnval[2] < -20.0):
        returnval[2] = -20.0
#    if t > 0.5 and t < 0.75:
#        returnval[2] = returnval[2] + 0.1
#    print(returnval)
    torque_vector.append(returnval)
    time_vector.append(t)
    return returnval