533 lines
20 KiB
Python
533 lines
20 KiB
Python
from sympy import solve
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from sympy.core.backend import (cos, expand, Matrix, sin, symbols, tan, sqrt, S,
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zeros, eye)
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from sympy.simplify.simplify import simplify
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from sympy.physics.mechanics import (dynamicsymbols, ReferenceFrame, Point,
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RigidBody, KanesMethod, inertia, Particle,
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dot)
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from sympy.testing.pytest import raises
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from sympy.core.backend import USE_SYMENGINE
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def test_invalid_coordinates():
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# Simple pendulum, but use symbols instead of dynamicsymbols
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l, m, g = symbols('l m g')
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q, u = symbols('q u') # Generalized coordinate
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kd = [q.diff(dynamicsymbols._t) - u]
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N, O = ReferenceFrame('N'), Point('O')
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O.set_vel(N, 0)
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P = Particle('P', Point('P'), m)
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P.point.set_pos(O, l * (sin(q) * N.x - cos(q) * N.y))
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F = (P.point, -m * g * N.y)
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raises(ValueError, lambda: KanesMethod(N, [q], [u], kd, bodies=[P],
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forcelist=[F]))
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def test_one_dof():
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# This is for a 1 dof spring-mass-damper case.
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# It is described in more detail in the KanesMethod docstring.
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q, u = dynamicsymbols('q u')
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qd, ud = dynamicsymbols('q u', 1)
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m, c, k = symbols('m c k')
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N = ReferenceFrame('N')
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P = Point('P')
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P.set_vel(N, u * N.x)
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kd = [qd - u]
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FL = [(P, (-k * q - c * u) * N.x)]
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pa = Particle('pa', P, m)
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BL = [pa]
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KM = KanesMethod(N, [q], [u], kd)
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KM.kanes_equations(BL, FL)
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assert KM.bodies == BL
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assert KM.loads == FL
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MM = KM.mass_matrix
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forcing = KM.forcing
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rhs = MM.inv() * forcing
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assert expand(rhs[0]) == expand(-(q * k + u * c) / m)
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assert simplify(KM.rhs() -
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KM.mass_matrix_full.LUsolve(KM.forcing_full)) == zeros(2, 1)
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assert (KM.linearize(A_and_B=True, )[0] == Matrix([[0, 1], [-k/m, -c/m]]))
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def test_two_dof():
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# This is for a 2 d.o.f., 2 particle spring-mass-damper.
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# The first coordinate is the displacement of the first particle, and the
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# second is the relative displacement between the first and second
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# particles. Speeds are defined as the time derivatives of the particles.
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q1, q2, u1, u2 = dynamicsymbols('q1 q2 u1 u2')
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q1d, q2d, u1d, u2d = dynamicsymbols('q1 q2 u1 u2', 1)
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m, c1, c2, k1, k2 = symbols('m c1 c2 k1 k2')
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N = ReferenceFrame('N')
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P1 = Point('P1')
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P2 = Point('P2')
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P1.set_vel(N, u1 * N.x)
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P2.set_vel(N, (u1 + u2) * N.x)
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# Note we multiply the kinematic equation by an arbitrary factor
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# to test the implicit vs explicit kinematics attribute
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kd = [q1d/2 - u1/2, 2*q2d - 2*u2]
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# Now we create the list of forces, then assign properties to each
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# particle, then create a list of all particles.
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FL = [(P1, (-k1 * q1 - c1 * u1 + k2 * q2 + c2 * u2) * N.x), (P2, (-k2 *
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q2 - c2 * u2) * N.x)]
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pa1 = Particle('pa1', P1, m)
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pa2 = Particle('pa2', P2, m)
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BL = [pa1, pa2]
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# Finally we create the KanesMethod object, specify the inertial frame,
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# pass relevant information, and form Fr & Fr*. Then we calculate the mass
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# matrix and forcing terms, and finally solve for the udots.
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KM = KanesMethod(N, q_ind=[q1, q2], u_ind=[u1, u2], kd_eqs=kd)
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KM.kanes_equations(BL, FL)
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MM = KM.mass_matrix
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forcing = KM.forcing
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rhs = MM.inv() * forcing
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assert expand(rhs[0]) == expand((-k1 * q1 - c1 * u1 + k2 * q2 + c2 * u2)/m)
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assert expand(rhs[1]) == expand((k1 * q1 + c1 * u1 - 2 * k2 * q2 - 2 *
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c2 * u2) / m)
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# Check that the explicit form is the default and kinematic mass matrix is identity
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assert KM.explicit_kinematics
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assert KM.mass_matrix_kin == eye(2)
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# Check that for the implicit form the mass matrix is not identity
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KM.explicit_kinematics = False
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assert KM.mass_matrix_kin == Matrix([[S(1)/2, 0], [0, 2]])
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# Check that whether using implicit or explicit kinematics the RHS
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# equations are consistent with the matrix form
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for explicit_kinematics in [False, True]:
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KM.explicit_kinematics = explicit_kinematics
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assert simplify(KM.rhs() -
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KM.mass_matrix_full.LUsolve(KM.forcing_full)) == zeros(4, 1)
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# Make sure an error is raised if nonlinear kinematic differential
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# equations are supplied.
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kd = [q1d - u1**2, sin(q2d) - cos(u2)]
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raises(ValueError, lambda: KanesMethod(N, q_ind=[q1, q2],
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u_ind=[u1, u2], kd_eqs=kd))
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def test_pend():
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q, u = dynamicsymbols('q u')
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qd, ud = dynamicsymbols('q u', 1)
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m, l, g = symbols('m l g')
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N = ReferenceFrame('N')
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P = Point('P')
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P.set_vel(N, -l * u * sin(q) * N.x + l * u * cos(q) * N.y)
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kd = [qd - u]
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FL = [(P, m * g * N.x)]
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pa = Particle('pa', P, m)
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BL = [pa]
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KM = KanesMethod(N, [q], [u], kd)
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KM.kanes_equations(BL, FL)
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MM = KM.mass_matrix
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forcing = KM.forcing
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rhs = MM.inv() * forcing
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rhs.simplify()
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assert expand(rhs[0]) == expand(-g / l * sin(q))
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assert simplify(KM.rhs() -
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KM.mass_matrix_full.LUsolve(KM.forcing_full)) == zeros(2, 1)
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def test_rolling_disc():
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# Rolling Disc Example
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# Here the rolling disc is formed from the contact point up, removing the
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# need to introduce generalized speeds. Only 3 configuration and three
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# speed variables are need to describe this system, along with the disc's
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# mass and radius, and the local gravity (note that mass will drop out).
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q1, q2, q3, u1, u2, u3 = dynamicsymbols('q1 q2 q3 u1 u2 u3')
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q1d, q2d, q3d, u1d, u2d, u3d = dynamicsymbols('q1 q2 q3 u1 u2 u3', 1)
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r, m, g = symbols('r m g')
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# The kinematics are formed by a series of simple rotations. Each simple
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# rotation creates a new frame, and the next rotation is defined by the new
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# frame's basis vectors. This example uses a 3-1-2 series of rotations, or
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# Z, X, Y series of rotations. Angular velocity for this is defined using
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# the second frame's basis (the lean frame).
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N = ReferenceFrame('N')
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Y = N.orientnew('Y', 'Axis', [q1, N.z])
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L = Y.orientnew('L', 'Axis', [q2, Y.x])
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R = L.orientnew('R', 'Axis', [q3, L.y])
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w_R_N_qd = R.ang_vel_in(N)
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R.set_ang_vel(N, u1 * L.x + u2 * L.y + u3 * L.z)
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# This is the translational kinematics. We create a point with no velocity
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# in N; this is the contact point between the disc and ground. Next we form
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# the position vector from the contact point to the disc's center of mass.
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# Finally we form the velocity and acceleration of the disc.
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C = Point('C')
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C.set_vel(N, 0)
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Dmc = C.locatenew('Dmc', r * L.z)
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Dmc.v2pt_theory(C, N, R)
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# This is a simple way to form the inertia dyadic.
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I = inertia(L, m / 4 * r**2, m / 2 * r**2, m / 4 * r**2)
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# Kinematic differential equations; how the generalized coordinate time
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# derivatives relate to generalized speeds.
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kd = [dot(R.ang_vel_in(N) - w_R_N_qd, uv) for uv in L]
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# Creation of the force list; it is the gravitational force at the mass
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# center of the disc. Then we create the disc by assigning a Point to the
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# center of mass attribute, a ReferenceFrame to the frame attribute, and mass
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# and inertia. Then we form the body list.
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ForceList = [(Dmc, - m * g * Y.z)]
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BodyD = RigidBody('BodyD', Dmc, R, m, (I, Dmc))
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BodyList = [BodyD]
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# Finally we form the equations of motion, using the same steps we did
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# before. Specify inertial frame, supply generalized speeds, supply
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# kinematic differential equation dictionary, compute Fr from the force
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# list and Fr* from the body list, compute the mass matrix and forcing
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# terms, then solve for the u dots (time derivatives of the generalized
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# speeds).
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KM = KanesMethod(N, q_ind=[q1, q2, q3], u_ind=[u1, u2, u3], kd_eqs=kd)
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KM.kanes_equations(BodyList, ForceList)
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MM = KM.mass_matrix
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forcing = KM.forcing
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rhs = MM.inv() * forcing
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kdd = KM.kindiffdict()
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rhs = rhs.subs(kdd)
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rhs.simplify()
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assert rhs.expand() == Matrix([(6*u2*u3*r - u3**2*r*tan(q2) +
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4*g*sin(q2))/(5*r), -2*u1*u3/3, u1*(-2*u2 + u3*tan(q2))]).expand()
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assert simplify(KM.rhs() -
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KM.mass_matrix_full.LUsolve(KM.forcing_full)) == zeros(6, 1)
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# This code tests our output vs. benchmark values. When r=g=m=1, the
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# critical speed (where all eigenvalues of the linearized equations are 0)
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# is 1 / sqrt(3) for the upright case.
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A = KM.linearize(A_and_B=True)[0]
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A_upright = A.subs({r: 1, g: 1, m: 1}).subs({q1: 0, q2: 0, q3: 0, u1: 0, u3: 0})
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import sympy
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assert sympy.sympify(A_upright.subs({u2: 1 / sqrt(3)})).eigenvals() == {S.Zero: 6}
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def test_aux():
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# Same as above, except we have 2 auxiliary speeds for the ground contact
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# point, which is known to be zero. In one case, we go through then
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# substitute the aux. speeds in at the end (they are zero, as well as their
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# derivative), in the other case, we use the built-in auxiliary speed part
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# of KanesMethod. The equations from each should be the same.
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q1, q2, q3, u1, u2, u3 = dynamicsymbols('q1 q2 q3 u1 u2 u3')
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q1d, q2d, q3d, u1d, u2d, u3d = dynamicsymbols('q1 q2 q3 u1 u2 u3', 1)
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u4, u5, f1, f2 = dynamicsymbols('u4, u5, f1, f2')
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u4d, u5d = dynamicsymbols('u4, u5', 1)
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r, m, g = symbols('r m g')
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N = ReferenceFrame('N')
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Y = N.orientnew('Y', 'Axis', [q1, N.z])
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L = Y.orientnew('L', 'Axis', [q2, Y.x])
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R = L.orientnew('R', 'Axis', [q3, L.y])
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w_R_N_qd = R.ang_vel_in(N)
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R.set_ang_vel(N, u1 * L.x + u2 * L.y + u3 * L.z)
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C = Point('C')
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C.set_vel(N, u4 * L.x + u5 * (Y.z ^ L.x))
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Dmc = C.locatenew('Dmc', r * L.z)
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Dmc.v2pt_theory(C, N, R)
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Dmc.a2pt_theory(C, N, R)
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I = inertia(L, m / 4 * r**2, m / 2 * r**2, m / 4 * r**2)
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kd = [dot(R.ang_vel_in(N) - w_R_N_qd, uv) for uv in L]
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ForceList = [(Dmc, - m * g * Y.z), (C, f1 * L.x + f2 * (Y.z ^ L.x))]
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BodyD = RigidBody('BodyD', Dmc, R, m, (I, Dmc))
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BodyList = [BodyD]
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KM = KanesMethod(N, q_ind=[q1, q2, q3], u_ind=[u1, u2, u3, u4, u5],
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kd_eqs=kd)
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(fr, frstar) = KM.kanes_equations(BodyList, ForceList)
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fr = fr.subs({u4d: 0, u5d: 0}).subs({u4: 0, u5: 0})
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frstar = frstar.subs({u4d: 0, u5d: 0}).subs({u4: 0, u5: 0})
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KM2 = KanesMethod(N, q_ind=[q1, q2, q3], u_ind=[u1, u2, u3], kd_eqs=kd,
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u_auxiliary=[u4, u5])
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(fr2, frstar2) = KM2.kanes_equations(BodyList, ForceList)
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fr2 = fr2.subs({u4d: 0, u5d: 0}).subs({u4: 0, u5: 0})
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frstar2 = frstar2.subs({u4d: 0, u5d: 0}).subs({u4: 0, u5: 0})
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frstar.simplify()
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frstar2.simplify()
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assert (fr - fr2).expand() == Matrix([0, 0, 0, 0, 0])
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assert (frstar - frstar2).expand() == Matrix([0, 0, 0, 0, 0])
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def test_parallel_axis():
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# This is for a 2 dof inverted pendulum on a cart.
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# This tests the parallel axis code in KanesMethod. The inertia of the
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# pendulum is defined about the hinge, not about the center of mass.
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# Defining the constants and knowns of the system
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gravity = symbols('g')
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k, ls = symbols('k ls')
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a, mA, mC = symbols('a mA mC')
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F = dynamicsymbols('F')
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Ix, Iy, Iz = symbols('Ix Iy Iz')
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# Declaring the Generalized coordinates and speeds
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q1, q2 = dynamicsymbols('q1 q2')
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q1d, q2d = dynamicsymbols('q1 q2', 1)
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u1, u2 = dynamicsymbols('u1 u2')
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u1d, u2d = dynamicsymbols('u1 u2', 1)
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# Creating reference frames
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N = ReferenceFrame('N')
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A = ReferenceFrame('A')
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A.orient(N, 'Axis', [-q2, N.z])
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A.set_ang_vel(N, -u2 * N.z)
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# Origin of Newtonian reference frame
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O = Point('O')
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# Creating and Locating the positions of the cart, C, and the
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# center of mass of the pendulum, A
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C = O.locatenew('C', q1 * N.x)
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Ao = C.locatenew('Ao', a * A.y)
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# Defining velocities of the points
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O.set_vel(N, 0)
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C.set_vel(N, u1 * N.x)
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Ao.v2pt_theory(C, N, A)
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Cart = Particle('Cart', C, mC)
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Pendulum = RigidBody('Pendulum', Ao, A, mA, (inertia(A, Ix, Iy, Iz), C))
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# kinematical differential equations
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kindiffs = [q1d - u1, q2d - u2]
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bodyList = [Cart, Pendulum]
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forceList = [(Ao, -N.y * gravity * mA),
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(C, -N.y * gravity * mC),
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(C, -N.x * k * (q1 - ls)),
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(C, N.x * F)]
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km = KanesMethod(N, [q1, q2], [u1, u2], kindiffs)
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(fr, frstar) = km.kanes_equations(bodyList, forceList)
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mm = km.mass_matrix_full
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assert mm[3, 3] == Iz
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def test_input_format():
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# 1 dof problem from test_one_dof
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q, u = dynamicsymbols('q u')
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qd, ud = dynamicsymbols('q u', 1)
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m, c, k = symbols('m c k')
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N = ReferenceFrame('N')
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P = Point('P')
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P.set_vel(N, u * N.x)
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kd = [qd - u]
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FL = [(P, (-k * q - c * u) * N.x)]
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pa = Particle('pa', P, m)
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BL = [pa]
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KM = KanesMethod(N, [q], [u], kd)
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# test for input format kane.kanes_equations((body1, body2, particle1))
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assert KM.kanes_equations(BL)[0] == Matrix([0])
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# test for input format kane.kanes_equations(bodies=(body1, body 2), loads=(load1,load2))
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assert KM.kanes_equations(bodies=BL, loads=None)[0] == Matrix([0])
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# test for input format kane.kanes_equations(bodies=(body1, body 2), loads=None)
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assert KM.kanes_equations(BL, loads=None)[0] == Matrix([0])
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# test for input format kane.kanes_equations(bodies=(body1, body 2))
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assert KM.kanes_equations(BL)[0] == Matrix([0])
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# test for input format kane.kanes_equations(bodies=(body1, body2), loads=[])
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assert KM.kanes_equations(BL, [])[0] == Matrix([0])
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# test for error raised when a wrong force list (in this case a string) is provided
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raises(ValueError, lambda: KM._form_fr('bad input'))
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# 1 dof problem from test_one_dof with FL & BL in instance
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KM = KanesMethod(N, [q], [u], kd, bodies=BL, forcelist=FL)
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assert KM.kanes_equations()[0] == Matrix([-c*u - k*q])
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# 2 dof problem from test_two_dof
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q1, q2, u1, u2 = dynamicsymbols('q1 q2 u1 u2')
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q1d, q2d, u1d, u2d = dynamicsymbols('q1 q2 u1 u2', 1)
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m, c1, c2, k1, k2 = symbols('m c1 c2 k1 k2')
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N = ReferenceFrame('N')
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P1 = Point('P1')
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P2 = Point('P2')
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P1.set_vel(N, u1 * N.x)
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P2.set_vel(N, (u1 + u2) * N.x)
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kd = [q1d - u1, q2d - u2]
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FL = ((P1, (-k1 * q1 - c1 * u1 + k2 * q2 + c2 * u2) * N.x), (P2, (-k2 *
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q2 - c2 * u2) * N.x))
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pa1 = Particle('pa1', P1, m)
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pa2 = Particle('pa2', P2, m)
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BL = (pa1, pa2)
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KM = KanesMethod(N, q_ind=[q1, q2], u_ind=[u1, u2], kd_eqs=kd)
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# test for input format
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# kane.kanes_equations((body1, body2), (load1, load2))
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KM.kanes_equations(BL, FL)
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MM = KM.mass_matrix
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forcing = KM.forcing
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rhs = MM.inv() * forcing
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assert expand(rhs[0]) == expand((-k1 * q1 - c1 * u1 + k2 * q2 + c2 * u2)/m)
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assert expand(rhs[1]) == expand((k1 * q1 + c1 * u1 - 2 * k2 * q2 - 2 *
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c2 * u2) / m)
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def test_implicit_kinematics():
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# Test that implicit kinematics can handle complicated
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# equations that explicit form struggles with
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# See https://github.com/sympy/sympy/issues/22626
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# Inertial frame
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NED = ReferenceFrame('NED')
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NED_o = Point('NED_o')
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NED_o.set_vel(NED, 0)
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# body frame
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q_att = dynamicsymbols('lambda_0:4', real=True)
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B = NED.orientnew('B', 'Quaternion', q_att)
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# Generalized coordinates
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q_pos = dynamicsymbols('B_x:z')
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B_cm = NED_o.locatenew('B_cm', q_pos[0]*B.x + q_pos[1]*B.y + q_pos[2]*B.z)
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q_ind = q_att[1:] + q_pos
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q_dep = [q_att[0]]
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kinematic_eqs = []
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# Generalized velocities
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B_ang_vel = B.ang_vel_in(NED)
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P, Q, R = dynamicsymbols('P Q R')
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B.set_ang_vel(NED, P*B.x + Q*B.y + R*B.z)
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B_ang_vel_kd = (B.ang_vel_in(NED) - B_ang_vel).simplify()
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# Equating the two gives us the kinematic equation
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kinematic_eqs += [
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B_ang_vel_kd & B.x,
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B_ang_vel_kd & B.y,
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B_ang_vel_kd & B.z
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]
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|
|
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B_cm_vel = B_cm.vel(NED)
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U, V, W = dynamicsymbols('U V W')
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B_cm.set_vel(NED, U*B.x + V*B.y + W*B.z)
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# Compute the velocity of the point using the two methods
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B_ref_vel_kd = (B_cm.vel(NED) - B_cm_vel)
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|
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# taking dot product with unit vectors to get kinematic equations
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# relating body coordinates and velocities
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|
|
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# Note, there is a choice to dot with NED.xyz here. That makes
|
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# the implicit form have some bigger terms but is still fine, the
|
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# explicit form still struggles though
|
|
kinematic_eqs += [
|
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B_ref_vel_kd & B.x,
|
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B_ref_vel_kd & B.y,
|
|
B_ref_vel_kd & B.z,
|
|
]
|
|
|
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u_ind = [U, V, W, P, Q, R]
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|
|
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# constraints
|
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q_att_vec = Matrix(q_att)
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config_cons = [(q_att_vec.T*q_att_vec)[0] - 1] #unit norm
|
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kinematic_eqs = kinematic_eqs + [(q_att_vec.T * q_att_vec.diff())[0]]
|
|
|
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try:
|
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KM = KanesMethod(NED, q_ind, u_ind,
|
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q_dependent= q_dep,
|
|
kd_eqs = kinematic_eqs,
|
|
configuration_constraints = config_cons,
|
|
velocity_constraints= [],
|
|
u_dependent= [], #no dependent speeds
|
|
u_auxiliary = [], # No auxiliary speeds
|
|
explicit_kinematics = False # implicit kinematics
|
|
)
|
|
except Exception as e:
|
|
# symengine struggles with these kinematic equations
|
|
if USE_SYMENGINE and 'Matrix is rank deficient' in str(e):
|
|
return
|
|
else:
|
|
raise e
|
|
|
|
# mass and inertia dyadic relative to CM
|
|
M_B = symbols('M_B')
|
|
J_B = inertia(B, *[S(f'J_B_{ax}')*(1 if ax[0] == ax[1] else -1)
|
|
for ax in ['xx', 'yy', 'zz', 'xy', 'yz', 'xz']])
|
|
J_B = J_B.subs({S('J_B_xy'): 0, S('J_B_yz'): 0})
|
|
RB = RigidBody('RB', B_cm, B, M_B, (J_B, B_cm))
|
|
|
|
rigid_bodies = [RB]
|
|
# Forces
|
|
force_list = [
|
|
#gravity pointing down
|
|
(RB.masscenter, RB.mass*S('g')*NED.z),
|
|
#generic forces and torques in body frame(inputs)
|
|
(RB.frame, dynamicsymbols('T_z')*B.z),
|
|
(RB.masscenter, dynamicsymbols('F_z')*B.z)
|
|
]
|
|
|
|
KM.kanes_equations(rigid_bodies, force_list)
|
|
|
|
# Expecting implicit form to be less than 5% of the flops
|
|
n_ops_implicit = sum(
|
|
[x.count_ops() for x in KM.forcing_full] +
|
|
[x.count_ops() for x in KM.mass_matrix_full]
|
|
)
|
|
# Save implicit kinematic matrices to use later
|
|
mass_matrix_kin_implicit = KM.mass_matrix_kin
|
|
forcing_kin_implicit = KM.forcing_kin
|
|
|
|
KM.explicit_kinematics = True
|
|
n_ops_explicit = sum(
|
|
[x.count_ops() for x in KM.forcing_full] +
|
|
[x.count_ops() for x in KM.mass_matrix_full]
|
|
)
|
|
forcing_kin_explicit = KM.forcing_kin
|
|
|
|
assert n_ops_implicit / n_ops_explicit < .05
|
|
|
|
# Ideally we would check that implicit and explicit equations give the same result as done in test_one_dof
|
|
# But the whole raison-d'etre of the implicit equations is to deal with problems such
|
|
# as this one where the explicit form is too complicated to handle, especially the angular part
|
|
# (i.e. tests would be too slow)
|
|
# Instead, we check that the kinematic equations are correct using more fundamental tests:
|
|
#
|
|
# (1) that we recover the kinematic equations we have provided
|
|
assert (mass_matrix_kin_implicit * KM.q.diff() - forcing_kin_implicit) == Matrix(kinematic_eqs)
|
|
|
|
# (2) that rate of quaternions matches what 'textbook' solutions give
|
|
# Note that we just use the explicit kinematics for the linear velocities
|
|
# as they are not as complicated as the angular ones
|
|
qdot_candidate = forcing_kin_explicit
|
|
|
|
quat_dot_textbook = Matrix([
|
|
[0, -P, -Q, -R],
|
|
[P, 0, R, -Q],
|
|
[Q, -R, 0, P],
|
|
[R, Q, -P, 0],
|
|
]) * q_att_vec / 2
|
|
|
|
# Again, if we don't use this "textbook" solution
|
|
# sympy will struggle to deal with the terms related to quaternion rates
|
|
# due to the number of operations involved
|
|
qdot_candidate[-1] = quat_dot_textbook[0] # lambda_0, note the [-1] as sympy's Kane puts the dependent coordinate last
|
|
qdot_candidate[0] = quat_dot_textbook[1] # lambda_1
|
|
qdot_candidate[1] = quat_dot_textbook[2] # lambda_2
|
|
qdot_candidate[2] = quat_dot_textbook[3] # lambda_3
|
|
|
|
# sub the config constraint in the candidate solution and compare to the implicit rhs
|
|
lambda_0_sol = solve(config_cons[0], q_att_vec[0])[1]
|
|
lhs_candidate = simplify(mass_matrix_kin_implicit * qdot_candidate).subs({q_att_vec[0]: lambda_0_sol})
|
|
assert lhs_candidate == forcing_kin_implicit
|