robust_calibration.GaussMarkovBiasModel Class Reference

Public Member Functions
	__init__ (self, float tau_fast=1.0, float tau_medium=100.0, float tau_slow=1e4, float process_noise=1e-4)
None	propagate (self, float dt)
None	update (self, float residual, float sigma_meas, float dt)
float	bias_contribution (self)
float	bias_variance (self)

Public Attributes
	tau = np.array([tau_fast, tau_medium, tau_slow])
	b = np.zeros(3)
float	P_b = np.eye(3) * 0.01
	process_noise = process_noise
	h = np.ones(3)

Protected Attributes
float	_last_t = 0.0

Detailed Description

Paper Section 4: Stochastic bias db/dt = -b/τ_b + w_b.
3-state bias: τ_fast=1s, τ_medium=100s, τ_slow=10⁴s.
Discrete: b_{k+1} = Φ_b b_k + w_b.

Definition at line 41 of file robust_calibration.py.

Constructor & Destructor Documentation

__init__()

robust_calibration.GaussMarkovBiasModel.__init__	(		self,
		float	tau_fast = 1.0,
		float	tau_medium = 100.0,
		float	tau_slow = 1e4,
		float	process_noise = 1e-4 )

Definition at line 48 of file robust_calibration.py.

Member Function Documentation

bias_contribution()

float robust_calibration.GaussMarkovBiasModel.bias_contribution

(

self

)

h'b for pressure prediction.

Definition at line 78 of file robust_calibration.py.

References APSR_Type.b, CONTROL_Type.b, IPSR_Type.b, b, xPSR_Type.b, fsw::control::RobustDDPController::NavState.h, and h.

bias_variance()

float robust_calibration.GaussMarkovBiasModel.bias_variance

(

self

)

h' Σ_b h for uncertainty.

Definition at line 82 of file robust_calibration.py.

References fsw::control::RobustDDPController::NavState.h, h, and P_b.

propagate()

None robust_calibration.GaussMarkovBiasModel.propagate	(		self,
		float	dt )

b_{k+1} = Φ_b b_k, P_{k+1} = Φ_b P Φ_b' + Q.

Definition at line 62 of file robust_calibration.py.

References APSR_Type.b, CONTROL_Type.b, IPSR_Type.b, b, xPSR_Type.b, P_b, process_noise, and tau.

Referenced by update().

update()

None robust_calibration.GaussMarkovBiasModel.update	(		self,
		float	residual,
		float	sigma_meas,
		float	dt )

Innovation update: residual = y_obs - (φ'θ + h'b).

Definition at line 70 of file robust_calibration.py.

References APSR_Type.b, CONTROL_Type.b, IPSR_Type.b, b, xPSR_Type.b, fsw::control::RobustDDPController::NavState.h, h, max, P_b, and propagate().

Referenced by combined_gui.PressureBarWidget.set_global_line_ys(), combined_gui.PressureBarWidget.set_limits(), and combined_gui.PressureBarWidget.set_value().

Member Data Documentation

_last_t

float robust_calibration.GaussMarkovBiasModel._last_t = 0.0

protected

Definition at line 59 of file robust_calibration.py.

b

robust_calibration.GaussMarkovBiasModel.b = np.zeros(3)

Definition at line 56 of file robust_calibration.py.

Referenced by bias_contribution(), propagate(), and update().

h

robust_calibration.GaussMarkovBiasModel.h = np.ones(3)

Definition at line 60 of file robust_calibration.py.

Referenced by engine.control.robust_ddp.data_models.NavState.__post_init__(), bias_contribution(), bias_variance(), engine.core.injectors.impinging._RingManifold.march(), test_injector_layout.TestChannels.test_channel_flow_area_is_reported_against_the_orifices(), test_injector_layout.TestContouredFace.test_clearances_are_to_the_groove_edges(), test_injector_layout.TestContouredFace.test_each_exit_is_square_on_its_flank(), test_injector_layout.TestContouredFace.test_exits_share_one_recessed_plane(), test_injector_layout.TestContouredFace.test_flat_face_keeps_the_old_geometry(), test_injector_layout.TestContouredFace.test_free_jet_is_measured_along_the_jet(), test_injector_layout.TestContouredFace.test_groove_edges_and_depth(), test_injector_layout.TestChannels.test_passage_runs_its_L_over_d_to_the_channel_floor(), test_injector_layout.TestContouredFace.test_the_jets_meet_where_trigonometry_says(), engine.control.robust_ddp.data_models.NavState.to_dict(), and update().

P_b

float robust_calibration.GaussMarkovBiasModel.P_b = np.eye(3) * 0.01

Definition at line 57 of file robust_calibration.py.

Referenced by bias_variance(), propagate(), and update().

process_noise

robust_calibration.GaussMarkovBiasModel.process_noise = process_noise

Definition at line 58 of file robust_calibration.py.

Referenced by propagate().

tau

robust_calibration.GaussMarkovBiasModel.tau = np.array([tau_fast, tau_medium, tau_slow])

Definition at line 55 of file robust_calibration.py.

Referenced by propagate().

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The documentation for this class was generated from the following file:

• daq-server/tools/calibration/robust_calibration.py