GaussianProcessGuider Class Reference

#include <gaussian_process_guider.h>

Classes
struct	guide_parameters

Public Member Functions
	GaussianProcessGuider (guide_parameters parameters)
void	add_one_point ()
double	deduceResult (double time_step, double prediction_point=-1.0)
void	DirectMoveApplied (double amt, double rate)
data_point &	get_last_point () const
size_t	get_number_of_measurements () const
data_point &	get_second_last_point () const
bool	GetBoolComputePeriod () const
double	GetControlGain () const
std::vector< double >	GetGPHyperparameters () const
double	GetMinMove () const
int	GetNumPointsForApproximation () const
double	GetPeriodLengthsInference () const
double	GetPeriodLengthsPeriodEstimation () const
double	getPredictionContribution ()
double	GetPredictionGain () const
void	GuidingDithered (double amt, double rate)
void	GuidingDitherSettleDone (bool success)
void	inject_data_point (double timestamp, double input, double SNR, double control)
Eigen::MatrixXd	regularize_dataset (const Eigen::VectorXd &timestamps, const Eigen::VectorXd &gear_error, const Eigen::VectorXd &variances)
void	reset ()
double	result (double input, double SNR, double time_step, double prediction_point=-1.0)
void	save_gp_data () const
bool	SetBoolComputePeriod (bool active)
bool	SetControlGain (double control_gain)
bool	SetGPHyperparameters (const std::vector< double > &hyperparameters)
void	SetLearningRate (double learning_rate)
bool	SetMinMove (double min_move)
bool	SetNumPointsForApproximation (int num_points)
bool	SetPeriodLengthsInference (double num_periods)
bool	SetPeriodLengthsPeriodEstimation (double num_periods)
bool	SetPredictionGain (double)
void	UpdateGP (double prediction_point=std::numeric_limits< double >::quiet_NaN())
void	UpdatePeriodLength (double period_length)

Detailed Description

This class provides a guiding algorithm for the right ascension axis that learns and predicts the periodic gear error with a Gaussian process.

This prediction helps reducing periodic error components in the residual tracking error. Further it is able to perform tracking without measurement to increase robustness of the overall guiding system.

Definition at line 47 of file gaussian_process_guider.h.

Member Function Documentation

deduceResult()

double GaussianProcessGuider::deduceResult	(	double	time_step,
		double	prediction_point = -1.0
	)

This method provides predictive control if no measurement could be made.

A zero measurement is stored with high uncertainty, and then the GP prediction is used for control.

Definition at line 385 of file gaussian_process_guider.cpp.

DirectMoveApplied()

void GaussianProcessGuider::DirectMoveApplied	(	double	amt,
		double	rate
	)

This method tells the guider that a direct move was issued.

This has the opposite effect of a dither on the dither offset.

Definition at line 464 of file gaussian_process_guider.cpp.

getPredictionContribution()

double GaussianProcessGuider::getPredictionContribution ( )

inline

Returns the weight of the prediction on the output control value.

Definition at line 253 of file gaussian_process_guider.h.

GuidingDithered()

void GaussianProcessGuider::GuidingDithered	(	double	amt,
		double	rate
	)

This method tells the guider that a dither command was issued.

The guider will stop collecting measurements and uses predictions instead, to keep the FFT and the GP working.

Definition at line 441 of file gaussian_process_guider.cpp.

GuidingDitherSettleDone()

void GaussianProcessGuider::GuidingDitherSettleDone

(

bool

success

)

This method tells the guider that dithering is finished.

The guider will resume normal operation.

Definition at line 453 of file gaussian_process_guider.cpp.

inject_data_point()

void GaussianProcessGuider::inject_data_point	(	double	timestamp,
		double	input,
		double	SNR,
		double	control
	)

This method is needed for automated testing.

It can inject data points.

Definition at line 590 of file gaussian_process_guider.cpp.

regularize_dataset()

Eigen::MatrixXd GaussianProcessGuider::regularize_dataset	(	const Eigen::VectorXd &	timestamps,
		const Eigen::VectorXd &	gear_error,
		const Eigen::VectorXd &	variances
	)

Takes timestamps, measurements and SNRs and returns them regularized in a matrix.

Definition at line 707 of file gaussian_process_guider.cpp.

reset()

void GaussianProcessGuider::reset

(

)

Clears the data from the circular buffer and clears the GP data.

Definition at line 421 of file gaussian_process_guider.cpp.

result()

double GaussianProcessGuider::result	(	double	input,
		double	SNR,
		double	time_step,
		double	prediction_point = -1.0
	)

Calculates the control value based on the current input.

1. The input is stored, 2. the GP is updated with the new data point, 3. the prediction is calculated to compensate the gear error and 4. the controller is calculated, consisting of feedback and prediction parts.

Definition at line 267 of file gaussian_process_guider.cpp.

save_gp_data()

void GaussianProcessGuider::save_gp_data

(

)

const

Saves the GP data to a csv file for external analysis.

Expensive!

Definition at line 774 of file gaussian_process_guider.cpp.

SetLearningRate()

void GaussianProcessGuider::SetLearningRate

(

double

learning_rate

)

Sets the learning rate.

Useful for disabling it for testing.

Definition at line 849 of file gaussian_process_guider.cpp.

UpdateGP()

void GaussianProcessGuider::UpdateGP

(

double

prediction_point = std::numeric_limits<double>::quiet_NaN()

)

Runs the inference machinery on the GP.

Gets the measurement data from the circular buffer and stores it in Eigen::Vectors. Detrends the data with linear regression. Calculates the main frequency with an FFT. Updates the GP accordingly with new data and parameter.

Definition at line 138 of file gaussian_process_guider.cpp.

UpdatePeriodLength()

void GaussianProcessGuider::UpdatePeriodLength

(

double

period_length

)

Does filtering and sets the period length of the GPGuider.

Definition at line 688 of file gaussian_process_guider.cpp.

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

• gaussian_process_guider.h
• gaussian_process_guider.cpp