120 lines
4.2 KiB
Python
120 lines
4.2 KiB
Python
import math
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import numpy as np
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from cereal import log
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from common.filter_simple import FirstOrderFilter
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from common.numpy_fast import clip, interp
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from common.realtime import DT_CTRL
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from selfdrive.controls.lib.latcontrol import LatControl, MIN_STEER_SPEED
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class LatControlINDI(LatControl):
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def __init__(self, CP, CI):
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super().__init__(CP, CI)
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self.angle_steers_des = 0.
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A = np.array([[1.0, DT_CTRL, 0.0],
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[0.0, 1.0, DT_CTRL],
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[0.0, 0.0, 1.0]])
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C = np.array([[1.0, 0.0, 0.0],
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[0.0, 1.0, 0.0]])
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# Q = np.matrix([[1e-2, 0.0, 0.0], [0.0, 1.0, 0.0], [0.0, 0.0, 10.0]])
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# R = np.matrix([[1e-2, 0.0], [0.0, 1e3]])
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# (x, l, K) = control.dare(np.transpose(A), np.transpose(C), Q, R)
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# K = np.transpose(K)
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K = np.array([[7.30262179e-01, 2.07003658e-04],
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[7.29394177e+00, 1.39159419e-02],
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[1.71022442e+01, 3.38495381e-02]])
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self.speed = 0.
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self.K = K
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self.A_K = A - np.dot(K, C)
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self.x = np.array([[0.], [0.], [0.]])
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self._RC = (CP.lateralTuning.indi.timeConstantBP, CP.lateralTuning.indi.timeConstantV)
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self._G = (CP.lateralTuning.indi.actuatorEffectivenessBP, CP.lateralTuning.indi.actuatorEffectivenessV)
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self._outer_loop_gain = (CP.lateralTuning.indi.outerLoopGainBP, CP.lateralTuning.indi.outerLoopGainV)
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self._inner_loop_gain = (CP.lateralTuning.indi.innerLoopGainBP, CP.lateralTuning.indi.innerLoopGainV)
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self.steer_filter = FirstOrderFilter(0., self.RC, DT_CTRL)
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self.reset()
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@property
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def RC(self):
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return interp(self.speed, self._RC[0], self._RC[1])
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@property
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def G(self):
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return interp(self.speed, self._G[0], self._G[1])
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@property
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def outer_loop_gain(self):
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return interp(self.speed, self._outer_loop_gain[0], self._outer_loop_gain[1])
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@property
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def inner_loop_gain(self):
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return interp(self.speed, self._inner_loop_gain[0], self._inner_loop_gain[1])
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def reset(self):
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super().reset()
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self.steer_filter.x = 0.
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self.speed = 0.
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def update(self, active, CS, CP, VM, params, last_actuators, desired_curvature, desired_curvature_rate):
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self.speed = CS.vEgo
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# Update Kalman filter
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y = np.array([[math.radians(CS.steeringAngleDeg)], [math.radians(CS.steeringRateDeg)]])
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self.x = np.dot(self.A_K, self.x) + np.dot(self.K, y)
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indi_log = log.ControlsState.LateralINDIState.new_message()
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indi_log.steeringAngleDeg = math.degrees(self.x[0])
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indi_log.steeringRateDeg = math.degrees(self.x[1])
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indi_log.steeringAccelDeg = math.degrees(self.x[2])
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steers_des = VM.get_steer_from_curvature(-desired_curvature, CS.vEgo, params.roll)
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steers_des += math.radians(params.angleOffsetDeg)
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indi_log.steeringAngleDesiredDeg = math.degrees(steers_des)
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rate_des = VM.get_steer_from_curvature(-desired_curvature_rate, CS.vEgo, 0)
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indi_log.steeringRateDesiredDeg = math.degrees(rate_des)
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if CS.vEgo < MIN_STEER_SPEED or not active:
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indi_log.active = False
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self.steer_filter.x = 0.0
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output_steer = 0
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else:
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# Expected actuator value
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self.steer_filter.update_alpha(self.RC)
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self.steer_filter.update(last_actuators.steer)
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# Compute acceleration error
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rate_sp = self.outer_loop_gain * (steers_des - self.x[0]) + rate_des
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accel_sp = self.inner_loop_gain * (rate_sp - self.x[1])
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accel_error = accel_sp - self.x[2]
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# Compute change in actuator
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g_inv = 1. / self.G
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delta_u = g_inv * accel_error
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# If steering pressed, only allow wind down
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if CS.steeringPressed and (delta_u * last_actuators.steer > 0):
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delta_u = 0
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output_steer = self.steer_filter.x + delta_u
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output_steer = clip(output_steer, -self.steer_max, self.steer_max)
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indi_log.active = True
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indi_log.rateSetPoint = float(rate_sp)
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indi_log.accelSetPoint = float(accel_sp)
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indi_log.accelError = float(accel_error)
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indi_log.delayedOutput = float(self.steer_filter.x)
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indi_log.delta = float(delta_u)
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indi_log.output = float(output_steer)
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indi_log.saturated = self._check_saturation(self.steer_max - abs(output_steer) < 1e-3, CS)
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return float(output_steer), float(steers_des), indi_log
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