Austin Schuh | 82a66dc | 2017-03-04 15:06:44 -0800 | [diff] [blame] | 1 | #!/usr/bin/python |
| 2 | |
John Park | 33858a3 | 2018-09-28 23:05:48 -0700 | [diff] [blame] | 3 | from aos.util.trapezoid_profile import TrapezoidProfile |
Austin Schuh | 82a66dc | 2017-03-04 15:06:44 -0800 | [diff] [blame] | 4 | from frc971.control_loops.python import control_loop |
| 5 | from frc971.control_loops.python import controls |
| 6 | from y2017.control_loops.python import turret |
| 7 | from y2017.control_loops.python import indexer |
| 8 | import numpy |
| 9 | import sys |
Austin Schuh | 82a66dc | 2017-03-04 15:06:44 -0800 | [diff] [blame] | 10 | from matplotlib import pylab |
| 11 | import gflags |
| 12 | import glog |
| 13 | |
| 14 | FLAGS = gflags.FLAGS |
| 15 | |
| 16 | try: |
Tyler Chatow | 6738c36 | 2019-02-16 14:12:30 -0800 | [diff] [blame] | 17 | gflags.DEFINE_bool('plot', False, 'If true, plot the loop response.') |
Austin Schuh | 82a66dc | 2017-03-04 15:06:44 -0800 | [diff] [blame] | 18 | except gflags.DuplicateFlagError: |
Tyler Chatow | 6738c36 | 2019-02-16 14:12:30 -0800 | [diff] [blame] | 19 | pass |
Austin Schuh | 82a66dc | 2017-03-04 15:06:44 -0800 | [diff] [blame] | 20 | |
| 21 | |
Austin Schuh | 82a66dc | 2017-03-04 15:06:44 -0800 | [diff] [blame] | 22 | class ColumnController(control_loop.ControlLoop): |
Austin Schuh | 82a66dc | 2017-03-04 15:06:44 -0800 | [diff] [blame] | 23 | |
Tyler Chatow | 6738c36 | 2019-02-16 14:12:30 -0800 | [diff] [blame] | 24 | def __init__(self, name='Column'): |
| 25 | super(ColumnController, self).__init__(name) |
| 26 | self.turret = turret.Turret(name + 'Turret') |
| 27 | self.indexer = indexer.Indexer(name + 'Indexer') |
Austin Schuh | 82a66dc | 2017-03-04 15:06:44 -0800 | [diff] [blame] | 28 | |
Tyler Chatow | 6738c36 | 2019-02-16 14:12:30 -0800 | [diff] [blame] | 29 | # Control loop time step |
| 30 | self.dt = 0.005 |
Austin Schuh | 82a66dc | 2017-03-04 15:06:44 -0800 | [diff] [blame] | 31 | |
Tyler Chatow | 6738c36 | 2019-02-16 14:12:30 -0800 | [diff] [blame] | 32 | # State is [position_indexer, |
| 33 | # velocity_indexer, |
| 34 | # position_shooter, |
| 35 | # velocity_shooter] |
| 36 | # Input is [volts_indexer, volts_shooter] |
| 37 | self.A_continuous = numpy.matrix(numpy.zeros((3, 3))) |
| 38 | self.B_continuous = numpy.matrix(numpy.zeros((3, 2))) |
Austin Schuh | 82a66dc | 2017-03-04 15:06:44 -0800 | [diff] [blame] | 39 | |
Tyler Chatow | 6738c36 | 2019-02-16 14:12:30 -0800 | [diff] [blame] | 40 | self.A_continuous[0, 0] = -( |
| 41 | self.indexer.Kt / self.indexer.Kv / |
| 42 | (self.indexer.J * self.indexer.resistance * self.indexer.G * |
| 43 | self.indexer.G) + self.turret.Kt / self.turret.Kv / |
| 44 | (self.indexer.J * self.turret.resistance * self.turret.G * |
| 45 | self.turret.G)) |
| 46 | self.A_continuous[0, 2] = self.turret.Kt / self.turret.Kv / ( |
| 47 | self.indexer.J * self.turret.resistance * self.turret.G * |
| 48 | self.turret.G) |
| 49 | self.B_continuous[0, 0] = self.indexer.Kt / ( |
| 50 | self.indexer.J * self.indexer.resistance * self.indexer.G) |
| 51 | self.B_continuous[0, 1] = -self.turret.Kt / ( |
| 52 | self.indexer.J * self.turret.resistance * self.turret.G) |
Austin Schuh | 82a66dc | 2017-03-04 15:06:44 -0800 | [diff] [blame] | 53 | |
Tyler Chatow | 6738c36 | 2019-02-16 14:12:30 -0800 | [diff] [blame] | 54 | self.A_continuous[1, 2] = 1 |
Austin Schuh | 82a66dc | 2017-03-04 15:06:44 -0800 | [diff] [blame] | 55 | |
Tyler Chatow | 6738c36 | 2019-02-16 14:12:30 -0800 | [diff] [blame] | 56 | self.A_continuous[2, 0] = self.turret.Kt / self.turret.Kv / ( |
| 57 | self.turret.J * self.turret.resistance * self.turret.G * |
| 58 | self.turret.G) |
| 59 | self.A_continuous[2, 2] = -self.turret.Kt / self.turret.Kv / ( |
| 60 | self.turret.J * self.turret.resistance * self.turret.G * |
| 61 | self.turret.G) |
Austin Schuh | 82a66dc | 2017-03-04 15:06:44 -0800 | [diff] [blame] | 62 | |
Tyler Chatow | 6738c36 | 2019-02-16 14:12:30 -0800 | [diff] [blame] | 63 | self.B_continuous[2, 1] = self.turret.Kt / ( |
| 64 | self.turret.J * self.turret.resistance * self.turret.G) |
Austin Schuh | 82a66dc | 2017-03-04 15:06:44 -0800 | [diff] [blame] | 65 | |
Tyler Chatow | 6738c36 | 2019-02-16 14:12:30 -0800 | [diff] [blame] | 66 | self.C = numpy.matrix([[1, 0, 0], [0, 1, 0]]) |
| 67 | self.D = numpy.matrix([[0, 0], [0, 0]]) |
Austin Schuh | 82a66dc | 2017-03-04 15:06:44 -0800 | [diff] [blame] | 68 | |
Tyler Chatow | 6738c36 | 2019-02-16 14:12:30 -0800 | [diff] [blame] | 69 | self.A, self.B = self.ContinuousToDiscrete(self.A_continuous, |
| 70 | self.B_continuous, self.dt) |
Austin Schuh | 82a66dc | 2017-03-04 15:06:44 -0800 | [diff] [blame] | 71 | |
Tyler Chatow | 6738c36 | 2019-02-16 14:12:30 -0800 | [diff] [blame] | 72 | q_indexer_vel = 13.0 |
| 73 | q_pos = 0.05 |
| 74 | q_vel = 0.8 |
| 75 | self.Q = numpy.matrix([[(1.0 / (q_indexer_vel**2.0)), 0.0, 0.0], |
| 76 | [0.0, (1.0 / (q_pos**2.0)), 0.0], |
| 77 | [0.0, 0.0, (1.0 / (q_vel**2.0))]]) |
Austin Schuh | 82a66dc | 2017-03-04 15:06:44 -0800 | [diff] [blame] | 78 | |
Tyler Chatow | 6738c36 | 2019-02-16 14:12:30 -0800 | [diff] [blame] | 79 | self.R = numpy.matrix([[(1.0 / (12.0**2.0)), 0.0], |
| 80 | [0.0, (1.0 / (12.0**2.0))]]) |
| 81 | self.K = controls.dlqr(self.A, self.B, self.Q, self.R) |
Austin Schuh | d5ccb86 | 2017-03-11 22:06:36 -0800 | [diff] [blame] | 82 | |
Tyler Chatow | 6738c36 | 2019-02-16 14:12:30 -0800 | [diff] [blame] | 83 | glog.debug('Controller poles are ' + |
| 84 | repr(numpy.linalg.eig(self.A - self.B * self.K)[0])) |
Austin Schuh | 82a66dc | 2017-03-04 15:06:44 -0800 | [diff] [blame] | 85 | |
Tyler Chatow | 6738c36 | 2019-02-16 14:12:30 -0800 | [diff] [blame] | 86 | q_vel_indexer_ff = 0.000005 |
| 87 | q_pos_ff = 0.0000005 |
| 88 | q_vel_ff = 0.00008 |
| 89 | self.Qff = numpy.matrix([[(1.0 / (q_vel_indexer_ff**2.0)), 0.0, 0.0], |
| 90 | [0.0, (1.0 / (q_pos_ff**2.0)), 0.0], |
| 91 | [0.0, 0.0, (1.0 / (q_vel_ff**2.0))]]) |
Austin Schuh | 82a66dc | 2017-03-04 15:06:44 -0800 | [diff] [blame] | 92 | |
Tyler Chatow | 6738c36 | 2019-02-16 14:12:30 -0800 | [diff] [blame] | 93 | self.Kff = controls.TwoStateFeedForwards(self.B, self.Qff) |
Austin Schuh | 82a66dc | 2017-03-04 15:06:44 -0800 | [diff] [blame] | 94 | |
Tyler Chatow | 6738c36 | 2019-02-16 14:12:30 -0800 | [diff] [blame] | 95 | self.U_max = numpy.matrix([[12.0], [12.0]]) |
| 96 | self.U_min = numpy.matrix([[-12.0], [-12.0]]) |
| 97 | |
| 98 | self.InitializeState() |
Austin Schuh | 82a66dc | 2017-03-04 15:06:44 -0800 | [diff] [blame] | 99 | |
| 100 | |
| 101 | class Column(ColumnController): |
Austin Schuh | 82a66dc | 2017-03-04 15:06:44 -0800 | [diff] [blame] | 102 | |
Tyler Chatow | 6738c36 | 2019-02-16 14:12:30 -0800 | [diff] [blame] | 103 | def __init__(self, name='Column', disable_indexer=False): |
| 104 | super(Column, self).__init__(name) |
| 105 | A_continuous = numpy.matrix(numpy.zeros((4, 4))) |
| 106 | B_continuous = numpy.matrix(numpy.zeros((4, 2))) |
Austin Schuh | 82a66dc | 2017-03-04 15:06:44 -0800 | [diff] [blame] | 107 | |
Tyler Chatow | 6738c36 | 2019-02-16 14:12:30 -0800 | [diff] [blame] | 108 | A_continuous[0, 1] = 1 |
| 109 | A_continuous[1:, 1:] = self.A_continuous |
| 110 | B_continuous[1:, :] = self.B_continuous |
Austin Schuh | 82a66dc | 2017-03-04 15:06:44 -0800 | [diff] [blame] | 111 | |
Tyler Chatow | 6738c36 | 2019-02-16 14:12:30 -0800 | [diff] [blame] | 112 | self.A_continuous = A_continuous |
| 113 | self.B_continuous = B_continuous |
Austin Schuh | 82a66dc | 2017-03-04 15:06:44 -0800 | [diff] [blame] | 114 | |
Tyler Chatow | 6738c36 | 2019-02-16 14:12:30 -0800 | [diff] [blame] | 115 | self.A, self.B = self.ContinuousToDiscrete(self.A_continuous, |
| 116 | self.B_continuous, self.dt) |
Austin Schuh | 82a66dc | 2017-03-04 15:06:44 -0800 | [diff] [blame] | 117 | |
Tyler Chatow | 6738c36 | 2019-02-16 14:12:30 -0800 | [diff] [blame] | 118 | self.C = numpy.matrix([[1, 0, 0, 0], [-1, 0, 1, 0]]) |
| 119 | self.D = numpy.matrix([[0, 0], [0, 0]]) |
Austin Schuh | 82a66dc | 2017-03-04 15:06:44 -0800 | [diff] [blame] | 120 | |
Tyler Chatow | 6738c36 | 2019-02-16 14:12:30 -0800 | [diff] [blame] | 121 | orig_K = self.K |
| 122 | self.K = numpy.matrix(numpy.zeros((2, 4))) |
| 123 | self.K[:, 1:] = orig_K |
Austin Schuh | d5ccb86 | 2017-03-11 22:06:36 -0800 | [diff] [blame] | 124 | |
Tyler Chatow | 6738c36 | 2019-02-16 14:12:30 -0800 | [diff] [blame] | 125 | glog.debug('K is ' + repr(self.K)) |
| 126 | # TODO(austin): Do we want to damp velocity out or not when disabled? |
| 127 | #if disable_indexer: |
| 128 | # self.K[0, 1] = 0.0 |
| 129 | # self.K[1, 1] = 0.0 |
Austin Schuh | 82a66dc | 2017-03-04 15:06:44 -0800 | [diff] [blame] | 130 | |
Tyler Chatow | 6738c36 | 2019-02-16 14:12:30 -0800 | [diff] [blame] | 131 | orig_Kff = self.Kff |
| 132 | self.Kff = numpy.matrix(numpy.zeros((2, 4))) |
| 133 | self.Kff[:, 1:] = orig_Kff |
Austin Schuh | 82a66dc | 2017-03-04 15:06:44 -0800 | [diff] [blame] | 134 | |
Tyler Chatow | 6738c36 | 2019-02-16 14:12:30 -0800 | [diff] [blame] | 135 | q_pos = 0.12 |
| 136 | q_vel = 2.00 |
| 137 | self.Q = numpy.matrix([[(q_pos**2.0), 0.0, 0.0, 0.0], |
| 138 | [0.0, (q_vel**2.0), 0.0, 0.0], |
| 139 | [0.0, 0.0, (q_pos**2.0), 0.0], |
| 140 | [0.0, 0.0, 0.0, (q_vel**2.0)]]) |
Austin Schuh | 82a66dc | 2017-03-04 15:06:44 -0800 | [diff] [blame] | 141 | |
Tyler Chatow | 6738c36 | 2019-02-16 14:12:30 -0800 | [diff] [blame] | 142 | r_pos = 0.05 |
| 143 | self.R = numpy.matrix([[(r_pos**2.0), 0.0], [0.0, (r_pos**2.0)]]) |
Austin Schuh | 82a66dc | 2017-03-04 15:06:44 -0800 | [diff] [blame] | 144 | |
Tyler Chatow | 6738c36 | 2019-02-16 14:12:30 -0800 | [diff] [blame] | 145 | self.KalmanGain, self.Q_steady = controls.kalman( |
| 146 | A=self.A, B=self.B, C=self.C, Q=self.Q, R=self.R) |
| 147 | self.L = self.A * self.KalmanGain |
| 148 | |
| 149 | self.InitializeState() |
Austin Schuh | 82a66dc | 2017-03-04 15:06:44 -0800 | [diff] [blame] | 150 | |
| 151 | |
| 152 | class IntegralColumn(Column): |
Austin Schuh | 82a66dc | 2017-03-04 15:06:44 -0800 | [diff] [blame] | 153 | |
Tyler Chatow | 6738c36 | 2019-02-16 14:12:30 -0800 | [diff] [blame] | 154 | def __init__(self, |
| 155 | name='IntegralColumn', |
| 156 | voltage_error_noise=None, |
| 157 | disable_indexer=False): |
| 158 | super(IntegralColumn, self).__init__(name) |
Austin Schuh | 82a66dc | 2017-03-04 15:06:44 -0800 | [diff] [blame] | 159 | |
Tyler Chatow | 6738c36 | 2019-02-16 14:12:30 -0800 | [diff] [blame] | 160 | A_continuous = numpy.matrix(numpy.zeros((6, 6))) |
| 161 | A_continuous[0:4, 0:4] = self.A_continuous |
| 162 | A_continuous[0:4:, 4:6] = self.B_continuous |
Austin Schuh | 82a66dc | 2017-03-04 15:06:44 -0800 | [diff] [blame] | 163 | |
Tyler Chatow | 6738c36 | 2019-02-16 14:12:30 -0800 | [diff] [blame] | 164 | B_continuous = numpy.matrix(numpy.zeros((6, 2))) |
| 165 | B_continuous[0:4, :] = self.B_continuous |
Austin Schuh | 82a66dc | 2017-03-04 15:06:44 -0800 | [diff] [blame] | 166 | |
Tyler Chatow | 6738c36 | 2019-02-16 14:12:30 -0800 | [diff] [blame] | 167 | self.A_continuous = A_continuous |
| 168 | self.B_continuous = B_continuous |
Austin Schuh | 82a66dc | 2017-03-04 15:06:44 -0800 | [diff] [blame] | 169 | |
Tyler Chatow | 6738c36 | 2019-02-16 14:12:30 -0800 | [diff] [blame] | 170 | self.A, self.B = self.ContinuousToDiscrete(self.A_continuous, |
| 171 | self.B_continuous, self.dt) |
Austin Schuh | 82a66dc | 2017-03-04 15:06:44 -0800 | [diff] [blame] | 172 | |
Tyler Chatow | 6738c36 | 2019-02-16 14:12:30 -0800 | [diff] [blame] | 173 | C = numpy.matrix(numpy.zeros((2, 6))) |
| 174 | C[0:2, 0:4] = self.C |
| 175 | self.C = C |
Austin Schuh | 82a66dc | 2017-03-04 15:06:44 -0800 | [diff] [blame] | 176 | |
Tyler Chatow | 6738c36 | 2019-02-16 14:12:30 -0800 | [diff] [blame] | 177 | self.D = numpy.matrix([[0, 0], [0, 0]]) |
Austin Schuh | d5ccb86 | 2017-03-11 22:06:36 -0800 | [diff] [blame] | 178 | |
Tyler Chatow | 6738c36 | 2019-02-16 14:12:30 -0800 | [diff] [blame] | 179 | orig_K = self.K |
| 180 | self.K = numpy.matrix(numpy.zeros((2, 6))) |
| 181 | self.K[:, 0:4] = orig_K |
Austin Schuh | 82a66dc | 2017-03-04 15:06:44 -0800 | [diff] [blame] | 182 | |
Tyler Chatow | 6738c36 | 2019-02-16 14:12:30 -0800 | [diff] [blame] | 183 | # TODO(austin): I'm not certain this is ideal. If someone spins the bottom |
| 184 | # at a constant rate, we'll learn a voltage offset. That should translate |
| 185 | # directly to a voltage on the turret to hold it steady. I'm also not |
| 186 | # convinced we care that much. If the indexer is off, it'll stop rather |
| 187 | # quickly anyways, so this is mostly a moot point. |
| 188 | if not disable_indexer: |
| 189 | self.K[0, 4] = 1 |
| 190 | self.K[1, 5] = 1 |
Austin Schuh | 82a66dc | 2017-03-04 15:06:44 -0800 | [diff] [blame] | 191 | |
Tyler Chatow | 6738c36 | 2019-02-16 14:12:30 -0800 | [diff] [blame] | 192 | orig_Kff = self.Kff |
| 193 | self.Kff = numpy.matrix(numpy.zeros((2, 6))) |
| 194 | self.Kff[:, 0:4] = orig_Kff |
Austin Schuh | 82a66dc | 2017-03-04 15:06:44 -0800 | [diff] [blame] | 195 | |
Tyler Chatow | 6738c36 | 2019-02-16 14:12:30 -0800 | [diff] [blame] | 196 | q_pos = 0.40 |
| 197 | q_vel = 2.00 |
| 198 | q_voltage = 8.0 |
| 199 | if voltage_error_noise is not None: |
| 200 | q_voltage = voltage_error_noise |
Austin Schuh | 82a66dc | 2017-03-04 15:06:44 -0800 | [diff] [blame] | 201 | |
Tyler Chatow | 6738c36 | 2019-02-16 14:12:30 -0800 | [diff] [blame] | 202 | self.Q = numpy.matrix([[(q_pos**2.0), 0.0, 0.0, 0.0, 0.0, 0.0], |
| 203 | [0.0, (q_vel**2.0), 0.0, 0.0, 0.0, 0.0], |
| 204 | [0.0, 0.0, (q_pos**2.0), 0.0, 0.0, 0.0], |
| 205 | [0.0, 0.0, 0.0, (q_vel**2.0), 0.0, 0.0], |
| 206 | [0.0, 0.0, 0.0, 0.0, (q_voltage**2.0), 0.0], |
| 207 | [0.0, 0.0, 0.0, 0.0, 0.0, (q_voltage**2.0)]]) |
Austin Schuh | 82a66dc | 2017-03-04 15:06:44 -0800 | [diff] [blame] | 208 | |
Tyler Chatow | 6738c36 | 2019-02-16 14:12:30 -0800 | [diff] [blame] | 209 | r_pos = 0.05 |
| 210 | self.R = numpy.matrix([[(r_pos**2.0), 0.0], [0.0, (r_pos**2.0)]]) |
Austin Schuh | 82a66dc | 2017-03-04 15:06:44 -0800 | [diff] [blame] | 211 | |
Tyler Chatow | 6738c36 | 2019-02-16 14:12:30 -0800 | [diff] [blame] | 212 | self.KalmanGain, self.Q_steady = controls.kalman( |
| 213 | A=self.A, B=self.B, C=self.C, Q=self.Q, R=self.R) |
| 214 | self.L = self.A * self.KalmanGain |
| 215 | |
| 216 | self.InitializeState() |
Austin Schuh | 82a66dc | 2017-03-04 15:06:44 -0800 | [diff] [blame] | 217 | |
| 218 | |
| 219 | class ScenarioPlotter(object): |
Austin Schuh | 82a66dc | 2017-03-04 15:06:44 -0800 | [diff] [blame] | 220 | |
Tyler Chatow | 6738c36 | 2019-02-16 14:12:30 -0800 | [diff] [blame] | 221 | def __init__(self): |
| 222 | # Various lists for graphing things. |
| 223 | self.t = [] |
| 224 | self.xi = [] |
| 225 | self.xt = [] |
| 226 | self.vi = [] |
| 227 | self.vt = [] |
| 228 | self.ai = [] |
| 229 | self.at = [] |
| 230 | self.x_hat = [] |
| 231 | self.ui = [] |
| 232 | self.ut = [] |
| 233 | self.ui_fb = [] |
| 234 | self.ut_fb = [] |
| 235 | self.offseti = [] |
| 236 | self.offsett = [] |
| 237 | self.turret_error = [] |
Austin Schuh | 82a66dc | 2017-03-04 15:06:44 -0800 | [diff] [blame] | 238 | |
Tyler Chatow | 6738c36 | 2019-02-16 14:12:30 -0800 | [diff] [blame] | 239 | def run_test(self, |
| 240 | column, |
| 241 | end_goal, |
| 242 | controller_column, |
| 243 | observer_column=None, |
| 244 | iterations=200): |
| 245 | """Runs the column plant with an initial condition and goal. |
Austin Schuh | 82a66dc | 2017-03-04 15:06:44 -0800 | [diff] [blame] | 246 | |
Tyler Chatow | 6738c36 | 2019-02-16 14:12:30 -0800 | [diff] [blame] | 247 | Args: |
| 248 | column: column object to use. |
| 249 | end_goal: end_goal state. |
| 250 | controller_column: Intake object to get K from, or None if we should |
| 251 | use column. |
| 252 | observer_column: Intake object to use for the observer, or None if we should |
| 253 | use the actual state. |
| 254 | iterations: Number of timesteps to run the model for. |
| 255 | """ |
Austin Schuh | 82a66dc | 2017-03-04 15:06:44 -0800 | [diff] [blame] | 256 | |
Tyler Chatow | 6738c36 | 2019-02-16 14:12:30 -0800 | [diff] [blame] | 257 | if controller_column is None: |
| 258 | controller_column = column |
Austin Schuh | 82a66dc | 2017-03-04 15:06:44 -0800 | [diff] [blame] | 259 | |
Tyler Chatow | 6738c36 | 2019-02-16 14:12:30 -0800 | [diff] [blame] | 260 | vbat = 12.0 |
Austin Schuh | 82a66dc | 2017-03-04 15:06:44 -0800 | [diff] [blame] | 261 | |
Tyler Chatow | 6738c36 | 2019-02-16 14:12:30 -0800 | [diff] [blame] | 262 | if self.t: |
| 263 | initial_t = self.t[-1] + column.dt |
| 264 | else: |
| 265 | initial_t = 0 |
Austin Schuh | 82a66dc | 2017-03-04 15:06:44 -0800 | [diff] [blame] | 266 | |
Tyler Chatow | 6738c36 | 2019-02-16 14:12:30 -0800 | [diff] [blame] | 267 | goal = numpy.concatenate((column.X, numpy.matrix(numpy.zeros((2, 1)))), |
| 268 | axis=0) |
Austin Schuh | 82a66dc | 2017-03-04 15:06:44 -0800 | [diff] [blame] | 269 | |
Tyler Chatow | 6738c36 | 2019-02-16 14:12:30 -0800 | [diff] [blame] | 270 | profile = TrapezoidProfile(column.dt) |
| 271 | profile.set_maximum_acceleration(10.0) |
| 272 | profile.set_maximum_velocity(3.0) |
| 273 | profile.SetGoal(goal[2, 0]) |
Austin Schuh | 82a66dc | 2017-03-04 15:06:44 -0800 | [diff] [blame] | 274 | |
Tyler Chatow | 6738c36 | 2019-02-16 14:12:30 -0800 | [diff] [blame] | 275 | U_last = numpy.matrix(numpy.zeros((2, 1))) |
Austin Schuh | 5ea4847 | 2021-02-02 20:46:41 -0800 | [diff] [blame^] | 276 | for i in range(iterations): |
Tyler Chatow | 6738c36 | 2019-02-16 14:12:30 -0800 | [diff] [blame] | 277 | observer_column.Y = column.Y |
| 278 | observer_column.CorrectObserver(U_last) |
Austin Schuh | 82a66dc | 2017-03-04 15:06:44 -0800 | [diff] [blame] | 279 | |
Tyler Chatow | 6738c36 | 2019-02-16 14:12:30 -0800 | [diff] [blame] | 280 | self.offseti.append(observer_column.X_hat[4, 0]) |
| 281 | self.offsett.append(observer_column.X_hat[5, 0]) |
| 282 | self.x_hat.append(observer_column.X_hat[0, 0]) |
Austin Schuh | 82a66dc | 2017-03-04 15:06:44 -0800 | [diff] [blame] | 283 | |
Tyler Chatow | 6738c36 | 2019-02-16 14:12:30 -0800 | [diff] [blame] | 284 | next_goal = numpy.concatenate( |
| 285 | (end_goal[0:2, :], profile.Update( |
| 286 | end_goal[2, 0], end_goal[3, 0]), end_goal[4:6, :]), |
| 287 | axis=0) |
Austin Schuh | 82a66dc | 2017-03-04 15:06:44 -0800 | [diff] [blame] | 288 | |
Tyler Chatow | 6738c36 | 2019-02-16 14:12:30 -0800 | [diff] [blame] | 289 | ff_U = controller_column.Kff * ( |
| 290 | next_goal - observer_column.A * goal) |
| 291 | fb_U = controller_column.K * (goal - observer_column.X_hat) |
| 292 | self.turret_error.append((goal[2, 0] - column.X[2, 0]) * 100.0) |
| 293 | self.ui_fb.append(fb_U[0, 0]) |
| 294 | self.ut_fb.append(fb_U[1, 0]) |
Austin Schuh | 82a66dc | 2017-03-04 15:06:44 -0800 | [diff] [blame] | 295 | |
Tyler Chatow | 6738c36 | 2019-02-16 14:12:30 -0800 | [diff] [blame] | 296 | U_uncapped = ff_U + fb_U |
Austin Schuh | 82a66dc | 2017-03-04 15:06:44 -0800 | [diff] [blame] | 297 | |
Tyler Chatow | 6738c36 | 2019-02-16 14:12:30 -0800 | [diff] [blame] | 298 | U = U_uncapped.copy() |
| 299 | U[0, 0] = numpy.clip(U[0, 0], -vbat, vbat) |
| 300 | U[1, 0] = numpy.clip(U[1, 0], -vbat, vbat) |
| 301 | self.xi.append(column.X[0, 0]) |
| 302 | self.xt.append(column.X[2, 0]) |
Austin Schuh | 82a66dc | 2017-03-04 15:06:44 -0800 | [diff] [blame] | 303 | |
Tyler Chatow | 6738c36 | 2019-02-16 14:12:30 -0800 | [diff] [blame] | 304 | if self.vi: |
| 305 | last_vi = self.vi[-1] |
| 306 | else: |
| 307 | last_vi = 0 |
| 308 | if self.vt: |
| 309 | last_vt = self.vt[-1] |
| 310 | else: |
| 311 | last_vt = 0 |
Austin Schuh | 82a66dc | 2017-03-04 15:06:44 -0800 | [diff] [blame] | 312 | |
Tyler Chatow | 6738c36 | 2019-02-16 14:12:30 -0800 | [diff] [blame] | 313 | self.vi.append(column.X[1, 0]) |
| 314 | self.vt.append(column.X[3, 0]) |
| 315 | self.ai.append((self.vi[-1] - last_vi) / column.dt) |
| 316 | self.at.append((self.vt[-1] - last_vt) / column.dt) |
Austin Schuh | 82a66dc | 2017-03-04 15:06:44 -0800 | [diff] [blame] | 317 | |
Tyler Chatow | 6738c36 | 2019-02-16 14:12:30 -0800 | [diff] [blame] | 318 | offset = 0.0 |
| 319 | if i > 100: |
| 320 | offset = 1.0 |
| 321 | column.Update(U + numpy.matrix([[0.0], [offset]])) |
Austin Schuh | 82a66dc | 2017-03-04 15:06:44 -0800 | [diff] [blame] | 322 | |
Tyler Chatow | 6738c36 | 2019-02-16 14:12:30 -0800 | [diff] [blame] | 323 | observer_column.PredictObserver(U) |
Austin Schuh | 82a66dc | 2017-03-04 15:06:44 -0800 | [diff] [blame] | 324 | |
Tyler Chatow | 6738c36 | 2019-02-16 14:12:30 -0800 | [diff] [blame] | 325 | self.t.append(initial_t + i * column.dt) |
| 326 | self.ui.append(U[0, 0]) |
| 327 | self.ut.append(U[1, 0]) |
Austin Schuh | 82a66dc | 2017-03-04 15:06:44 -0800 | [diff] [blame] | 328 | |
Tyler Chatow | 6738c36 | 2019-02-16 14:12:30 -0800 | [diff] [blame] | 329 | ff_U -= U_uncapped - U |
| 330 | goal = controller_column.A * goal + controller_column.B * ff_U |
Austin Schuh | 82a66dc | 2017-03-04 15:06:44 -0800 | [diff] [blame] | 331 | |
Tyler Chatow | 6738c36 | 2019-02-16 14:12:30 -0800 | [diff] [blame] | 332 | if U[1, 0] != U_uncapped[1, 0]: |
| 333 | profile.MoveCurrentState( |
| 334 | numpy.matrix([[goal[2, 0]], [goal[3, 0]]])) |
Austin Schuh | 82a66dc | 2017-03-04 15:06:44 -0800 | [diff] [blame] | 335 | |
Tyler Chatow | 6738c36 | 2019-02-16 14:12:30 -0800 | [diff] [blame] | 336 | glog.debug('Time: %f', self.t[-1]) |
| 337 | glog.debug('goal_error %s', repr((end_goal - goal).T)) |
| 338 | glog.debug('error %s', repr((observer_column.X_hat - end_goal).T)) |
Austin Schuh | 82a66dc | 2017-03-04 15:06:44 -0800 | [diff] [blame] | 339 | |
Tyler Chatow | 6738c36 | 2019-02-16 14:12:30 -0800 | [diff] [blame] | 340 | def Plot(self): |
| 341 | pylab.subplot(3, 1, 1) |
| 342 | pylab.plot(self.t, self.xi, label='x_indexer') |
| 343 | pylab.plot(self.t, self.xt, label='x_turret') |
| 344 | pylab.plot(self.t, self.x_hat, label='x_hat') |
| 345 | pylab.plot(self.t, self.turret_error, label='turret_error * 100') |
| 346 | pylab.legend() |
Austin Schuh | 82a66dc | 2017-03-04 15:06:44 -0800 | [diff] [blame] | 347 | |
Tyler Chatow | 6738c36 | 2019-02-16 14:12:30 -0800 | [diff] [blame] | 348 | pylab.subplot(3, 1, 2) |
| 349 | pylab.plot(self.t, self.ui, label='u_indexer') |
| 350 | pylab.plot(self.t, self.ui_fb, label='u_indexer_fb') |
| 351 | pylab.plot(self.t, self.ut, label='u_turret') |
| 352 | pylab.plot(self.t, self.ut_fb, label='u_turret_fb') |
| 353 | pylab.plot(self.t, self.offseti, label='voltage_offset_indexer') |
| 354 | pylab.plot(self.t, self.offsett, label='voltage_offset_turret') |
| 355 | pylab.legend() |
Austin Schuh | 82a66dc | 2017-03-04 15:06:44 -0800 | [diff] [blame] | 356 | |
Tyler Chatow | 6738c36 | 2019-02-16 14:12:30 -0800 | [diff] [blame] | 357 | pylab.subplot(3, 1, 3) |
| 358 | pylab.plot(self.t, self.ai, label='a_indexer') |
| 359 | pylab.plot(self.t, self.at, label='a_turret') |
| 360 | pylab.plot(self.t, self.vi, label='v_indexer') |
| 361 | pylab.plot(self.t, self.vt, label='v_turret') |
| 362 | pylab.legend() |
| 363 | |
| 364 | pylab.show() |
Austin Schuh | 82a66dc | 2017-03-04 15:06:44 -0800 | [diff] [blame] | 365 | |
| 366 | |
| 367 | def main(argv): |
Tyler Chatow | 6738c36 | 2019-02-16 14:12:30 -0800 | [diff] [blame] | 368 | scenario_plotter = ScenarioPlotter() |
Austin Schuh | 82a66dc | 2017-03-04 15:06:44 -0800 | [diff] [blame] | 369 | |
Tyler Chatow | 6738c36 | 2019-02-16 14:12:30 -0800 | [diff] [blame] | 370 | column = Column() |
| 371 | column_controller = IntegralColumn() |
| 372 | observer_column = IntegralColumn() |
Austin Schuh | 82a66dc | 2017-03-04 15:06:44 -0800 | [diff] [blame] | 373 | |
Tyler Chatow | 6738c36 | 2019-02-16 14:12:30 -0800 | [diff] [blame] | 374 | initial_X = numpy.matrix([[0.0], [0.0], [0.0], [0.0]]) |
| 375 | R = numpy.matrix([[0.0], [10.0], [5.0], [0.0], [0.0], [0.0]]) |
| 376 | scenario_plotter.run_test( |
| 377 | column, |
| 378 | end_goal=R, |
| 379 | controller_column=column_controller, |
| 380 | observer_column=observer_column, |
| 381 | iterations=400) |
Austin Schuh | 82a66dc | 2017-03-04 15:06:44 -0800 | [diff] [blame] | 382 | |
Tyler Chatow | 6738c36 | 2019-02-16 14:12:30 -0800 | [diff] [blame] | 383 | if FLAGS.plot: |
| 384 | scenario_plotter.Plot() |
Austin Schuh | 82a66dc | 2017-03-04 15:06:44 -0800 | [diff] [blame] | 385 | |
Tyler Chatow | 6738c36 | 2019-02-16 14:12:30 -0800 | [diff] [blame] | 386 | if len(argv) != 7: |
| 387 | glog.fatal('Expected .h file name and .cc file names') |
| 388 | else: |
| 389 | namespaces = ['y2017', 'control_loops', 'superstructure', 'column'] |
| 390 | column = Column('Column') |
| 391 | loop_writer = control_loop.ControlLoopWriter( |
| 392 | 'Column', [column], namespaces=namespaces) |
| 393 | loop_writer.AddConstant( |
| 394 | control_loop.Constant('kIndexerFreeSpeed', '%f', |
| 395 | column.indexer.free_speed)) |
| 396 | loop_writer.AddConstant( |
| 397 | control_loop.Constant('kIndexerOutputRatio', '%f', |
| 398 | column.indexer.G)) |
| 399 | loop_writer.AddConstant( |
| 400 | control_loop.Constant('kTurretFreeSpeed', '%f', |
| 401 | column.turret.free_speed)) |
| 402 | loop_writer.AddConstant( |
| 403 | control_loop.Constant('kTurretOutputRatio', '%f', column.turret.G)) |
| 404 | loop_writer.Write(argv[1], argv[2]) |
Austin Schuh | 82a66dc | 2017-03-04 15:06:44 -0800 | [diff] [blame] | 405 | |
Tyler Chatow | 6738c36 | 2019-02-16 14:12:30 -0800 | [diff] [blame] | 406 | # IntegralColumn controller 1 will disable the indexer. |
| 407 | integral_column = IntegralColumn('IntegralColumn') |
| 408 | disabled_integral_column = IntegralColumn( |
| 409 | 'DisabledIntegralColumn', disable_indexer=True) |
| 410 | integral_loop_writer = control_loop.ControlLoopWriter( |
| 411 | 'IntegralColumn', [integral_column, disabled_integral_column], |
| 412 | namespaces=namespaces) |
| 413 | integral_loop_writer.Write(argv[3], argv[4]) |
Austin Schuh | 82a66dc | 2017-03-04 15:06:44 -0800 | [diff] [blame] | 414 | |
Tyler Chatow | 6738c36 | 2019-02-16 14:12:30 -0800 | [diff] [blame] | 415 | stuck_integral_column = IntegralColumn( |
| 416 | 'StuckIntegralColumn', voltage_error_noise=8.0) |
| 417 | stuck_integral_loop_writer = control_loop.ControlLoopWriter( |
| 418 | 'StuckIntegralColumn', [stuck_integral_column], |
| 419 | namespaces=namespaces) |
| 420 | stuck_integral_loop_writer.Write(argv[5], argv[6]) |
Austin Schuh | 82a66dc | 2017-03-04 15:06:44 -0800 | [diff] [blame] | 421 | |
| 422 | |
| 423 | if __name__ == '__main__': |
Tyler Chatow | 6738c36 | 2019-02-16 14:12:30 -0800 | [diff] [blame] | 424 | argv = FLAGS(sys.argv) |
| 425 | glog.init() |
| 426 | sys.exit(main(argv)) |