API Reference

state_space_design.observerGainMatrixTool.cli

Command line interface for observerGainMatrixTool.

state_space_design.observerGainMatrixTool.cli.build_parser()

Return type:

ArgumentParser

state_space_design.observerGainMatrixTool.cli.main(argv=None)

Parameters:

argv (list[str] | None)

Return type:

int

state_space_design.observerGainMatrixTool.apis

class state_space_design.observerGainMatrixTool.apis.ObserverRequest(A: 'str', C: 'str', poles: 'List[complex]', method: 'str' = 'auto', place_fallback: 'str' = 'none', jitter_eps: 'float' = 1e-06, B: 'Optional[str]' = None, K: 'Optional[str]' = None, K_poles_csv: 'Optional[str]' = None, K_poles_list: 'Optional[List[str]]' = None, compute_closed_loop: 'bool' = False, x0: 'Optional[str]' = None, e0: 'Optional[str]' = None, t_final: 'float' = 0.0, dt: 'float' = 0.01, pretty: 'bool' = False, equations: 'bool' = False, eq_style: 'str' = 'auto', latex_out: 'Optional[str]' = None)

Bases: object

Parameters:

• A (str)

• C (str)

• poles (List[complex])

• method (str)

• place_fallback (str)

• jitter_eps (float)

• B (str | None)

• K (str | None)

• K_poles_csv (str | None)

• K_poles_list (List[str] | None)

• compute_closed_loop (bool)

• x0 (str | None)

• e0 (str | None)

• t_final (float)

• dt (float)

• pretty (bool)

• equations (bool)

• eq_style (str)

• latex_out (str | None)

A: str

B: str | None = None

C: str

K: str | None = None

K_poles_csv: str | None = None

K_poles_list: List[str] | None = None

compute_closed_loop: bool = False

dt: float = 0.01

e0: str | None = None

eq_style: str = 'auto'

equations: bool = False

jitter_eps: float = 1e-06

latex_out: str | None = None

method: str = 'auto'

place_fallback: str = 'none'

poles: List[complex]

pretty: bool = False

t_final: float = 0.0

x0: str | None = None

class state_space_design.observerGainMatrixTool.apis.ObserverResponse(data: 'Dict[str, Any]' = <factory>, pretty_blocks: 'List[str]' = <factory>)

Bases: object

Parameters:

• data (Dict[str, Any])

• pretty_blocks (List[str])

data: Dict[str, Any]

pretty_blocks: List[str]

state_space_design.observerGainMatrixTool.app

class state_space_design.observerGainMatrixTool.app.ObserverGainMatrixApp(out=<factory>)

Bases: object

Orchestrate observer gain design and optional reporting outputs.

Parameters:

out (OutputManager)

out: OutputManager

run(req)

Run the full observer-gain workflow and return structured results.

Parameters:

req (ObserverRequest)

Return type:

ObserverResponse

state_space_design.observerGainMatrixTool.app.build_augmented(A, B, C, K, Ke)

Build the augmented separation-structure state matrix.

Parameters:

• A (ndarray)

• B (ndarray)

• C (ndarray)

• K (ndarray)

• Ke (ndarray)

Return type:

ndarray

state_space_design.observerGainMatrixTool.app.latex_bmatrix(M)

Render a minimal LaTeX bmatrix string without a SymPy dependency.

Parameters:

M (ndarray)

Return type:

str

state_space_design.observerGainMatrixTool.app.latex_equation(A, B, C, Ke)

Build a display-math LaTeX snippet for the observer equation.

Parameters:

• A (ndarray)

• B (ndarray | None)

• C (ndarray)

• Ke (ndarray)

Return type:

str

state_space_design.observerGainMatrixTool.app.observer_controller_tf(A, B, C, K, Ke)

Compute the observer-controller transfer-function numerator and denominator.

Parameters:

• A (ndarray)

• B (ndarray)

• C (ndarray)

• K (ndarray)

• Ke (ndarray)

Return type:

Tuple[list, list]

state_space_design.observerGainMatrixTool.app.simulate_initial(A_aug, C, K, x0, e0, t_final, dt)

Simulate the zero-input augmented system by exact discretization.

Parameters:

• A_aug (ndarray)

• C (ndarray)

• K (ndarray)

• x0 (ndarray)

• e0 (ndarray)

• t_final (float)

• dt (float)

Return type:

Tuple[list, list, list, list, list]

state_space_design.observerGainMatrixTool.utils

state_space_design.observerGainMatrixTool.utils.jitter_repeated_poles(poles, eps)

Spread repeated real poles by a small amount for pole placement.

Parameters:

• poles (ndarray)

• eps (float)

Return type:

ndarray

state_space_design.observerGainMatrixTool.utils.parse_cplx_csv(s)

Parse comma-separated complex-number tokens.

Parameters:

s (str)

Return type:

ndarray

state_space_design.observerGainMatrixTool.utils.parse_cplx_tokens(tokens)

Parse complex-number tokens into a complex numpy array.

Parameters:

tokens (Sequence[str])

Return type:

ndarray

state_space_design.observerGainMatrixTool.utils.parse_matrix(s)

Parse a numeric matrix string into a float numpy array.

Parameters:

s (str)

Return type:

ndarray

state_space_design.observerGainMatrixTool.utils.parse_vector(s)

Parse a numeric vector string into a column vector.

Parameters:

s (str)

Return type:

ndarray

state_space_design.observerGainMatrixTool.utils.pole_multiplicities(poles, tol=0.0)

Count repeated real pole values within a tolerance.

Parameters:

• poles (ndarray)

• tol (float)

Return type:

Dict[float, int]

state_space_design.observerGainMatrixTool.utils.pretty_poly(coeffs, var='s')

Format polynomial coefficients as a compact plain text expression.

Parameters:

• coeffs (ndarray)

• var (str)

Return type:

str

state_space_design.observerGainMatrixTool.core

state_space_design.observerGainMatrixTool.core.ctrb_dual(A, C)

Parameters:

• A (ndarray)

• C (ndarray)

Return type:

ndarray

state_space_design.observerGainMatrixTool.core.ctrb_matrix(A, B)

Parameters:

• A (ndarray)

• B (ndarray)

Return type:

ndarray

state_space_design.observerGainMatrixTool.core.is_observable(A, C)

Parameters:

• A (ndarray)

• C (ndarray)

Return type:

bool

state_space_design.observerGainMatrixTool.core.obsv_matrix(A, C)

Parameters:

• A (ndarray)

• C (ndarray)

Return type:

ndarray

state_space_design.observerGainMatrixTool.core.phi_coeffs_from_poles(poles)

Parameters:

poles (ndarray)

Return type:

ndarray

state_space_design.observerGainMatrixTool.core.phi_of_matrix(A, poles)

Parameters:

• A (ndarray)

• poles (ndarray)

Return type:

ndarray

state_space_design.observerGainMatrixTool.io

class state_space_design.observerGainMatrixTool.io.OutputManager(out_dir: 'Path' = PosixPath('stateSpaceDesign/observerGainMatrixTool/out'))

Bases: object

Parameters:

out_dir (Path)

ensure()

Return type:

None

out_dir: Path = PosixPath('stateSpaceDesign/observerGainMatrixTool/out')

write_json(data, filename)

Parameters:

filename (str)

Return type:

Path

write_text(text, filename)

Parameters:

• text (str)

• filename (str)

Return type:

Path

state_space_design.observerGainMatrixTool.design

class state_space_design.observerGainMatrixTool.design.ControllerDesigner

Bases: object

State-feedback K via place() if available, else SISO Ackermann fallback.

compute_place(A, B, poles)

Parameters:

• A (ndarray)

• B (ndarray)

• poles (ndarray)

Return type:

ndarray

class state_space_design.observerGainMatrixTool.design.ObserverDesignResult(Ke: 'np.ndarray', method_used: 'str', meta: 'Dict[str, Any]')

Bases: object

Parameters:

• Ke (ndarray)

• method_used (str)

• meta (Dict[str, Any])

Ke: ndarray

meta: Dict[str, Any]

method_used: str

class state_space_design.observerGainMatrixTool.design.ObserverDesigner

Bases: object

Compute full-order observer gains K_e using ‘place’ (dual) or Ackermann.

compute(A, C, poles, method='auto', place_fallback='none', jitter_eps=1e-06)

Parameters:

• A (ndarray)

• C (ndarray)

• poles (ndarray)

• method (str)

• place_fallback (str)

• jitter_eps (float)

Return type:

ObserverDesignResult

method_ackermann_dual(A, C, poles)

Parameters:

• A (ndarray)

• C (ndarray)

• poles (ndarray)

Return type:

ndarray

method_place_dual(A, C, poles, place_fallback='none', jitter_eps=1e-06)

Parameters:

• A (ndarray)

• C (ndarray)

• poles (ndarray)

• place_fallback (str)

• jitter_eps (float)

Return type:

Tuple[ndarray, Dict[str, Any]]