# Canonical training model — unified sysid (cost 0.925, 475 generations).
# Source: sysid_result.json → exported via src.sysid.export.
# Key physics: ~96 ms motor lag (filter_tau), Stribeck friction, driver bias.
# Regenerate with:
#   python -m src.sysid.optimize --robot-path assets/rotary_cartpole --recording <capture>.npz
# then copy robot_tuned.yaml over this file once validated
# (python -m src.sysid.visualize to compare real vs sim).

urdf: rotary_cartpole_tuned.urdf

actuators:
  - joint: motor_joint
    type: motor
    gear: [0.846499, 1.183733]          # torque constant [pos, neg]
    ctrl_range: [-0.686251, 0.686251]   # PWM saturation (MAX_MOTOR_SPEED / 255)
    deadzone: [0.181097, 0.202072]      # L298N min |ctrl| for torque [pos, neg]
    damping: [0.013165, 0.015452]       # viscous damping [pos, neg]
    frictionloss: [0.014244, 0.001005]  # Coulomb friction [pos, neg]
    filter_tau: 0.096263                # 1st-order actuator lag (s) — dominant!
    stribeck_friction_boost: 0.068594   # extra static friction near standstill
    stribeck_vel: 5.279594              # Stribeck decay velocity (rad/s)
    action_bias: 0.056566               # additive ctrl bias (driver asymmetry)

joints:
  motor_joint:
    armature: 0.001676                  # reflected rotor inertia (kg·m²)
    frictionloss: 0.0                   # handled by motor model via qfrc_applied
  pendulum_joint:
    damping: 1.2e-05
    frictionloss: 7.2e-05