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Comran Morshede9b12922015-11-04 19:46:48 +00001#!/usr/bin/python
2
3import control_loop
4import controls
5import numpy
6import sys
7from matplotlib import pylab
8
9
10class CIM(control_loop.ControlLoop):
11 def __init__(self):
12 super(CIM, self).__init__("CIM")
13 # Stall Torque in N m
14 self.stall_torque = 2.42
15 # Stall Current in Amps
16 self.stall_current = 133
17 # Free Speed in RPM
18 self.free_speed = 4650.0
19 # Free Current in Amps
20 self.free_current = 2.7
21 # Moment of inertia of the CIM in kg m^2
22 self.J = 0.0001
23 # Resistance of the motor, divided by 2 to account for the 2 motors
24 self.R = 12.0 / self.stall_current
25 # Motor velocity constant
26 self.Kv = ((self.free_speed / 60.0 * 2.0 * numpy.pi) /
27 (12.0 - self.R * self.free_current))
28 # Torque constant
29 self.Kt = self.stall_torque / self.stall_current
30 # Control loop time step
31 self.dt = 0.005
32
33 # State feedback matrices
34 self.A_continuous = numpy.matrix(
35 [[-self.Kt / self.Kv / (self.J * self.R)]])
36 self.B_continuous = numpy.matrix(
37 [[self.Kt / (self.J * self.R)]])
38 self.C = numpy.matrix([[1]])
39 self.D = numpy.matrix([[0]])
40
41 self.A, self.B = self.ContinuousToDiscrete(self.A_continuous,
42 self.B_continuous, self.dt)
43
44 self.PlaceControllerPoles([0.01])
45 self.PlaceObserverPoles([0.01])
46
47 self.U_max = numpy.matrix([[12.0]])
48 self.U_min = numpy.matrix([[-12.0]])
49
50 self.InitializeState()
51
52
53class Drivetrain(control_loop.ControlLoop):
54 def __init__(self, name="Drivetrain", left_low=True, right_low=True):
55 super(Drivetrain, self).__init__(name)
56 # Stall Torque in N m
57 self.stall_torque = 2.42
58 # Stall Current in Amps
59 self.stall_current = 133
60 # Free Speed in RPM. Used number from last year.
61 self.free_speed = 4650.0
62 # Free Current in Amps
63 self.free_current = 2.7
64 # Moment of inertia of the drivetrain in kg m^2
65 # Just borrowed from last year.
66 self.J = 4.5
67 # Mass of the robot, in kg.
68 self.m = 60
69 # Radius of the robot, in meters (from last year).
70 self.rb = 0.7112 / 2.0
71 # Radius of the wheels, in meters.
72 self.r = .04445
73 # Resistance of the motor, divided by the number of motors.
74 self.R = 12.0 / self.stall_current / 4
75 # Motor velocity constant
76 self.Kv = ((self.free_speed / 60.0 * 2.0 * numpy.pi) /
77 (12.0 - self.R * self.free_current))
78 # Torque constant
79 self.Kt = self.stall_torque / self.stall_current
80 # Gear ratios
81 self.G_low = 14.0 / 60.0 * 17.0 / 50.0
82 self.G_high = 30.0 / 44.0 * 17.0 / 50.0
83 if left_low:
84 self.Gl = self.G_low
85 else:
86 self.Gl = self.G_high
87 if right_low:
88 self.Gr = self.G_low
89 else:
90 self.Gr = self.G_high
91 # Control loop time step
92 self.dt = 0.01
93
94 # These describe the way that a given side of a robot will be influenced
95 # by the other side. Units of 1 / kg.
96 self.msp = 1.0 / self.m + self.rb * self.rb / self.J
97 self.msn = 1.0 / self.m - self.rb * self.rb / self.J
98 # The calculations which we will need for A and B.
99 self.tcl = -self.Kt / self.Kv / (self.Gl * self.Gl * self.R * self.r * self.r)
100 self.tcr = -self.Kt / self.Kv / (self.Gr * self.Gr * self.R * self.r * self.r)
101 self.mpl = self.Kt / (self.Gl * self.R * self.r)
102 self.mpr = self.Kt / (self.Gr * self.R * self.r)
103
104 # State feedback matrices
105 # X will be of the format
106 # [[positionl], [velocityl], [positionr], velocityr]]
107 self.A_continuous = numpy.matrix(
108 [[0, 1, 0, 0],
109 [0, self.msp * self.tcl, 0, self.msn * self.tcr],
110 [0, 0, 0, 1],
111 [0, self.msn * self.tcl, 0, self.msp * self.tcr]])
112 self.B_continuous = numpy.matrix(
113 [[0, 0],
114 [self.msp * self.mpl, self.msn * self.mpr],
115 [0, 0],
116 [self.msn * self.mpl, self.msp * self.mpr]])
117 self.C = numpy.matrix([[1, 0, 0, 0],
118 [0, 0, 1, 0]])
119 self.D = numpy.matrix([[0, 0],
120 [0, 0]])
121
122 #print "THE NUMBER I WANT" + str(numpy.linalg.inv(self.A_continuous) * -self.B_continuous * numpy.matrix([[12.0], [12.0]]))
123 self.A, self.B = self.ContinuousToDiscrete(
124 self.A_continuous, self.B_continuous, self.dt)
125
126 # Poles from last year.
127 self.hp = 0.65
128 self.lp = 0.83
129 self.PlaceControllerPoles([self.hp, self.lp, self.hp, self.lp])
130 print self.K
131 q_pos = 0.07
132 q_vel = 1.0
133 self.Q = numpy.matrix([[(1.0 / (q_pos ** 2.0)), 0.0, 0.0, 0.0],
134 [0.0, (1.0 / (q_vel ** 2.0)), 0.0, 0.0],
135 [0.0, 0.0, (1.0 / (q_pos ** 2.0)), 0.0],
136 [0.0, 0.0, 0.0, (1.0 / (q_vel ** 2.0))]])
137
138 self.R = numpy.matrix([[(1.0 / (12.0 ** 2.0)), 0.0],
139 [0.0, (1.0 / (12.0 ** 2.0))]])
140 self.K = controls.dlqr(self.A, self.B, self.Q, self.R)
141 print self.A
142 print self.B
143 print self.K
144 print numpy.linalg.eig(self.A - self.B * self.K)[0]
145
146 self.hlp = 0.3
147 self.llp = 0.4
148 self.PlaceObserverPoles([self.hlp, self.hlp, self.llp, self.llp])
149
150 self.U_max = numpy.matrix([[12.0], [12.0]])
151 self.U_min = numpy.matrix([[-12.0], [-12.0]])
152 self.InitializeState()
153
154def main(argv):
155 # Simulate the response of the system to a step input.
156 drivetrain = Drivetrain()
157 simulated_left = []
158 simulated_right = []
159 for _ in xrange(100):
160 drivetrain.Update(numpy.matrix([[12.0], [12.0]]))
161 simulated_left.append(drivetrain.X[0, 0])
162 simulated_right.append(drivetrain.X[2, 0])
163
164 #pylab.plot(range(100), simulated_left)
165 #pylab.plot(range(100), simulated_right)
166 #pylab.show()
167
168 # Simulate forwards motion.
169 drivetrain = Drivetrain()
170 close_loop_left = []
171 close_loop_right = []
172 R = numpy.matrix([[1.0], [0.0], [1.0], [0.0]])
173 for _ in xrange(100):
174 U = numpy.clip(drivetrain.K * (R - drivetrain.X_hat),
175 drivetrain.U_min, drivetrain.U_max)
176 drivetrain.UpdateObserver(U)
177 drivetrain.Update(U)
178 close_loop_left.append(drivetrain.X[0, 0])
179 close_loop_right.append(drivetrain.X[2, 0])
180
181 #pylab.plot(range(100), close_loop_left)
182 #pylab.plot(range(100), close_loop_right)
183 #pylab.show()
184
185 # Try turning in place
186 drivetrain = Drivetrain()
187 close_loop_left = []
188 close_loop_right = []
189 R = numpy.matrix([[-1.0], [0.0], [1.0], [0.0]])
190 for _ in xrange(100):
191 U = numpy.clip(drivetrain.K * (R - drivetrain.X_hat),
192 drivetrain.U_min, drivetrain.U_max)
193 drivetrain.UpdateObserver(U)
194 drivetrain.Update(U)
195 close_loop_left.append(drivetrain.X[0, 0])
196 close_loop_right.append(drivetrain.X[2, 0])
197
198 #pylab.plot(range(100), close_loop_left)
199 #pylab.plot(range(100), close_loop_right)
200 #pylab.show()
201
202 # Try turning just one side.
203 drivetrain = Drivetrain()
204 close_loop_left = []
205 close_loop_right = []
206 R = numpy.matrix([[0.0], [0.0], [1.0], [0.0]])
207 for _ in xrange(100):
208 U = numpy.clip(drivetrain.K * (R - drivetrain.X_hat),
209 drivetrain.U_min, drivetrain.U_max)
210 drivetrain.UpdateObserver(U)
211 drivetrain.Update(U)
212 close_loop_left.append(drivetrain.X[0, 0])
213 close_loop_right.append(drivetrain.X[2, 0])
214
215 #pylab.plot(range(100), close_loop_left)
216 #pylab.plot(range(100), close_loop_right)
217 #pylab.show()
218
219 # Write the generated constants out to a file.
220 print "Output one"
221 drivetrain_low_low = Drivetrain(name="DrivetrainLowLow", left_low=True, right_low=True)
222 drivetrain_low_high = Drivetrain(name="DrivetrainLowHigh", left_low=True, right_low=False)
223 drivetrain_high_low = Drivetrain(name="DrivetrainHighLow", left_low=False, right_low=True)
224 drivetrain_high_high = Drivetrain(name="DrivetrainHighHigh", left_low=False, right_low=False)
225
226 if len(argv) != 3:
227 print "Expected .h file name and .cc file name"
228 else:
229 dog_loop_writer = control_loop.ControlLoopWriter(
230 "Drivetrain", [drivetrain_low_low, drivetrain_low_high,
231 drivetrain_high_low, drivetrain_high_high],
232 namespaces = ["bot3", "control_loops"])
233 if argv[1][-3:] == '.cc':
234 dog_loop_writer.Write(argv[2], argv[1])
235 else:
236 dog_loop_writer.Write(argv[1], argv[2])
237
238if __name__ == '__main__':
239 sys.exit(main(sys.argv))