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