icarus::staging::LinearModel Struct Reference

Linear state-space model. More...

#include <LinearModel.hpp>

Public Member Functions
void	ExportMatlab (const std::string &path) const
	Export to MATLAB .m file.
void	ExportNumPy (const std::string &path) const
	Export to Python/NumPy .py file.
void	ExportJSON (const std::string &path) const
	Export to JSON file.
int	ControllabilityRank () const
	Compute controllability matrix rank.
int	ObservabilityRank () const
	Compute observability matrix rank.
bool	IsStable () const
	Check if system is stable (all eigenvalues have negative real part).
Eigen::VectorXcd	Eigenvalues () const
	Get eigenvalues of A matrix.

Public Attributes
Eigen::MatrixXd	A
	State matrix (n_states x n_states).
Eigen::MatrixXd	B
	Input matrix (n_states x n_inputs).
Eigen::MatrixXd	C
	Output matrix (n_outputs x n_states).
Eigen::MatrixXd	D
	Feedthrough matrix (n_outputs x n_inputs).
std::vector< std::string >	state_names
std::vector< std::string >	input_names
std::vector< std::string >	output_names
Eigen::VectorXd	x0
	Operating point where linearization was performed.
Eigen::VectorXd	u0
double	t0 = 0.0

Detailed Description

Linear state-space model.

Represents the linearized system: x_dot = A*x + B*u y = C*x + D*u

Where x is the state deviation from x0, u is input deviation from u0.

Member Function Documentation

ControllabilityRank()

int icarus::staging::LinearModel::ControllabilityRank ( ) const

inlinenodiscard

Compute controllability matrix rank.

Controllability matrix: [B, AB, A^2B, ..., A^(n-1)B] System is controllable iff rank equals n_states.

Returns

Rank of controllability matrix, or 0 if no inputs (uncontrollable)

Eigenvalues()

Eigen::VectorXcd icarus::staging::LinearModel::Eigenvalues ( ) const

inlinenodiscard

Get eigenvalues of A matrix.

ExportJSON()

void icarus::staging::LinearModel::ExportJSON ( const std::string & path ) const

inline

Export to JSON file.

ExportMatlab()

void icarus::staging::LinearModel::ExportMatlab ( const std::string & path ) const

inline

Export to MATLAB .m file.

Creates a MATLAB script that defines A, B, C, D matrices and constructs an ss() state-space object.

ExportNumPy()

void icarus::staging::LinearModel::ExportNumPy ( const std::string & path ) const

inline

Export to Python/NumPy .py file.

IsStable()

bool icarus::staging::LinearModel::IsStable ( ) const

inlinenodiscard

Check if system is stable (all eigenvalues have negative real part).

ObservabilityRank()

int icarus::staging::LinearModel::ObservabilityRank ( ) const

inlinenodiscard

Compute observability matrix rank.

Observability matrix: [C; CA; CA^2; ...; CA^(n-1)] System is observable iff rank equals n_states.

Returns

Rank of observability matrix, or 0 if no outputs (unobservable)

Member Data Documentation

A

Eigen::MatrixXd icarus::staging::LinearModel::A

State matrix (n_states x n_states).

B

Eigen::MatrixXd icarus::staging::LinearModel::B

Input matrix (n_states x n_inputs).

C

Eigen::MatrixXd icarus::staging::LinearModel::C

Output matrix (n_outputs x n_states).

D

Eigen::MatrixXd icarus::staging::LinearModel::D

Feedthrough matrix (n_outputs x n_inputs).

input_names

std::vector<std::string> icarus::staging::LinearModel::input_names

output_names

std::vector<std::string> icarus::staging::LinearModel::output_names

state_names

std::vector<std::string> icarus::staging::LinearModel::state_names

t0

double icarus::staging::LinearModel::t0 = 0.0

u0

Eigen::VectorXd icarus::staging::LinearModel::u0

x0

Eigen::VectorXd icarus::staging::LinearModel::x0

Operating point where linearization was performed.

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

• include/icarus/staging/LinearModel.hpp