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Austin Schuh999a19e2024-05-04 14:52:39 -07001#!/usr/bin/python3
2
3import numpy
4import sympy
5import scipy.integrate
6from frc971.control_loops.python import control_loop
7from frc971.control_loops.python import controls
8
9from matplotlib import pylab
10import sys
11import gflags
12import glog
13
14FLAGS = gflags.FLAGS
15
16
17class SwerveSimulation(object):
18
19 def __init__(self):
20 self.motor = control_loop.KrakenFOC()
21
22 vx, vy, omega = sympy.symbols('vx vy omega')
23 fx, fy = sympy.symbols('fx fy')
24 t = sympy.symbols('t')
25
26 # 5kg of force got us a slip angle of 0.05 radians with 4 tires.
27 self.C = 5 * 9.8 / 0.05 / 4.0
28
29 self.r = 2 * 0.0254
30
31 # Base is 20kg without battery.
32 self.m = 25.0
33 self.G = 1.0 / 6.75
34
35 I = sympy.symbols('I')
36
37 # Absolute linear velocity in x and y of the robot.
38 self.dvx = (self.C * (self.r * omega - vx) / vx + fx) / self.m
39 self.dvy = (-self.C * sympy.atan2(vy, vx) + fy) / self.m
40 # Angular velocity of the wheel.
41 self.domega = (-self.G * self.C * (self.r * omega - vx) / vx * self.r +
42 self.motor.Kt * I) * self.G / self.motor.motor_inertia
43
44 self.x0 = sympy.lambdify((vx, vy, omega, fx, fy, I), self.dvx)
45 self.x1 = sympy.lambdify((vx, vy, omega, fx, fy, I), self.dvy)
46 self.x2 = sympy.lambdify((vx, vy, omega, fx, fy, I), self.domega)
47
48 self.f = lambda X, fx, fy, I: numpy.array([
49 self.x0(X[0], X[1], X[2], fx, fy, I),
50 self.x1(X[0], X[1], X[2], fx, fy, I),
51 self.x2(X[0], X[1], X[2], fx, fy, I)
52 ])
53
54 print(self.f)
55 print(
56 'f',
57 self.f(numpy.matrix([[1.0], [0.0], [1.0 / self.r]]), 0.0, 0.0,
58 0.0))
59
60 print(self.dvx)
61 print(self.dvy)
62 print(self.domega)
63
64 def run(self, X_initial):
65 print(X_initial)
66
67 fx = -9.8
68 fy = 0.0
69 I = -(fx * self.r * self.G / self.motor.Kt)
70 print(f"Fx: {fx}, Fy: {fy}, I: {I}")
71
72 def f_const(t, X):
73 return self.f(
74 X=X,
75 fx=fx,
76 fy=fy,
77 I=I,
78 )
79
80 result = scipy.integrate.solve_ivp(
81 f_const, (0, 2.0),
82 numpy.squeeze(numpy.array(X_initial.transpose())),
83 max_step=0.01)
84
85 pylab.plot(result.t, result.y[0, :], label="y0")
86 pylab.plot(result.t, result.y[1, :], label="y1")
87 pylab.plot(result.t, result.y[2, :], label="y2")
88
89 pylab.legend()
90 pylab.show()
91
92
93def main(argv):
94 s = SwerveSimulation()
95 s.run(numpy.matrix([[1.0], [0.0], [1.0 / s.r]]))
96
97 return 0
98
99
100if __name__ == '__main__':
101 argv = FLAGS(sys.argv)
102 glog.init()
103 sys.exit(main(argv))