PythonMutipleShooting/initialize_NMPC.py at main · Ameroro/PythonMutipleShooting · GitHub

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import numpy as np

def Initialize_NMPC():
    # Snake Model
    Nl = 5
    l = 0.18 / 2
    m = 1.56
    J = 1/3 * m * l**2
    ct = 4.45
    cn = 17.3
    mun = 2.57
    lambda1 = 5.26e-8
    lambda2 = 0.0120
    lambda3 = 8.1160e-04
    Vxc = -0.00
    Vyc = -0.00

    # NMPC Parameters
    N = 20
    M = 4
    T = 5
    Nstates = 2 * Nl + 4
    Ncontrols = Nl - 1
    x0 = np.zeros(2 * Nl + 4)

    # Store parameters for the use of constraint and objective function
    auxdata = {}
    auxdata['N'] = N
    auxdata['M'] = M
    auxdata['T'] = T
    auxdata['Nstates'] = Nstates
    auxdata['Ncontrols'] = Ncontrols
    auxdata['x0'] = x0

    SnakeModel = {}
    SnakeModel['Nl'] = Nl
    SnakeModel['l'] = l
    SnakeModel['m'] = m
    SnakeModel['J'] = J
    SnakeModel['ct'] = ct
    SnakeModel['cn'] = cn
    SnakeModel['mun'] = mun
    SnakeModel['lambda1'] = lambda1
    SnakeModel['lambda2'] = lambda2
    SnakeModel['lambda3'] = lambda3
    SnakeModel['Vxc'] = Vxc
    SnakeModel['Vyc'] = Vyc

    A = np.diag(np.ones(Nl), 0) + np.diag(np.ones(Nl - 1), 1)
    A = A[:Nl - 1, :]
    SnakeModel['A'] = A

    D = np.diag(np.ones(Nl), 0) - np.diag(np.ones(Nl - 1), 1)
    D = D[:Nl - 1, :]
    SnakeModel['D'] = D

    H = np.zeros((2 * Nl, 2 * Nl))
    for i in range(Nl):
        H[i, i:Nl] = 1
        H[Nl + i, Nl + i:2 * Nl] = 1
    SnakeModel['H'] = H
    SnakeModel['H_inv'] = np.linalg.inv(H)

    H_inv2 = np.zeros((Ncontrols, Nstates))
    H_inv2[:Nl - 1, :Nl] = SnakeModel['H_inv'][:Nl - 1, :Nl]
    SnakeModel['H_inv2'] = H_inv2

    SnakeModel['e'] = np.ones(Nl)
    SnakeModel['K'] = A.T @ (np.linalg.inv(D @ D.T) @ D)
    SnakeModel['V'] = A.T @ (np.linalg.inv(D @ D.T) @ A)

    return auxdata, SnakeModel