import numpy as np from common.realtime import DT_CTRL from selfdrive.car.body import bodycan from opendbc.can.packer import CANPacker from selfdrive.car.body.values import SPEED_FROM_RPM MAX_TORQUE = 500 MAX_TORQUE_RATE = 50 MAX_ANGLE_ERROR = 7 MAX_POS_INTEGRATOR = 0.2 # meters MAX_TURN_INTEGRATOR = 0.1 # meters class CarController(): def __init__(self, dbc_name, CP, VM): self.frame = 0 self.packer = CANPacker(dbc_name) self.i_speed = 0 self.i_speed_diff = 0 self.i_balance = 0 self.d_balance = 0 self.speed_measured = 0. self.speed_desired = 0. self.torque_r_filtered = 0. self.torque_l_filtered = 0. self.wait_counter = int(5. / DT_CTRL) @staticmethod def deadband_filter(torque, deadband): if torque > 0: torque += deadband else: torque -= deadband return torque def update(self, CC, CS): if self.wait_counter > 0: self.wait_counter -= 1 return CC.actuators.copy(), [] if len(CC.orientationNED) == 0 or len(CC.angularVelocity) == 0: return CC.actuators.copy(), [] # /////////////////////////////////////// # Steer and accel mixin. Speed should be used as a target? (speed should be in m/s! now it is in RPM) # Mix steer into torque_diff # self.steerRatio = 0.5 # torque_r = int(np.clip((CC.actuators.accel*1000) - (CC.actuators.steer*1000) * self.steerRatio, -1000, 1000)) # torque_l = int(np.clip((CC.actuators.accel*1000) + (CC.actuators.steer*1000) * self.steerRatio, -1000, 1000)) # //// # Setpoint speed PID kp_speed = 0.001 / SPEED_FROM_RPM ki_speed = 0.001 / SPEED_FROM_RPM alpha_speed = 1.0 self.speed_measured = SPEED_FROM_RPM * (CS.out.wheelSpeeds.fl + CS.out.wheelSpeeds.fr) / 2. self.speed_desired = (1. - alpha_speed) * self.speed_desired speed_error = self.speed_desired - self.speed_measured self.i_speed += speed_error * DT_CTRL self.i_speed = np.clip(self.i_speed, -MAX_POS_INTEGRATOR, MAX_POS_INTEGRATOR) set_point = kp_speed * speed_error + ki_speed * self.i_speed # Balancing PID kp_balance = 1300 ki_balance = 0 kd_balance = 280 # Clip angle error, this is enough to get up from stands p_balance = np.clip((-CC.orientationNED[1]) - set_point, np.radians(-MAX_ANGLE_ERROR), np.radians(MAX_ANGLE_ERROR)) self.i_balance += CS.out.wheelSpeeds.fl + CS.out.wheelSpeeds.fr self.d_balance = np.clip(-CC.angularVelocity[1], -1., 1.) torque = int(np.clip((p_balance*kp_balance + self.i_balance*ki_balance + self.d_balance*kd_balance), -1000, 1000)) # yaw recovery PID kp_turn = 0.1 / SPEED_FROM_RPM ki_turn = 0.1 / SPEED_FROM_RPM speed_diff_measured = SPEED_FROM_RPM * (CS.out.wheelSpeeds.fl - CS.out.wheelSpeeds.fr) self.i_speed_diff += speed_diff_measured * DT_CTRL self.i_speed_diff = np.clip(self.i_speed_diff, -MAX_TURN_INTEGRATOR, MAX_TURN_INTEGRATOR) torque_diff = int(np.clip(kp_turn * speed_diff_measured + ki_turn * self.i_speed_diff, -100, 100)) # Combine 2 PIDs outputs torque_r = torque + torque_diff torque_l = torque - torque_diff # Torque rate limits self.torque_r_filtered = np.clip(self.deadband_filter(torque_r, 10), self.torque_r_filtered - MAX_TORQUE_RATE, self.torque_r_filtered + MAX_TORQUE_RATE) self.torque_l_filtered = np.clip(self.deadband_filter(torque_l, 10), self.torque_l_filtered - MAX_TORQUE_RATE, self.torque_l_filtered + MAX_TORQUE_RATE) torque_r = int(np.clip(self.torque_r_filtered, -MAX_TORQUE, MAX_TORQUE)) torque_l = int(np.clip(self.torque_l_filtered, -MAX_TORQUE, MAX_TORQUE)) # /////////////////////////////////////// can_sends = [] can_sends.append(bodycan.create_control(self.packer, torque_l, torque_r, self.frame // 2)) new_actuators = CC.actuators.copy() new_actuators.accel = torque_l new_actuators.steer = torque_r self.frame += 1 return new_actuators, can_sends