Reference guides are available for functions and commands supported by OML, Tcl, and Python.
The Reference Guide contains documentation for all functions supported in the OpenMatrix language.
Discover new features and enhancements.
Discover Compose, including its language support and system requirements.
The Compose tutorials and associated example model files help introduce you to the basic functionality of the software.
Provides detailed information regarding the features and functionality available in Compose.
OpenMatrix is a mathematical scripting language.
Ackermann's formula (pole placement gain selection for single-input systems).
Appends the inputs and outputs of the two models.
Add states to the outputs of a state-space model.
Computes a Gramian balanced realization of an LTI model.
Block diagonalizability with the Schur factorization.
Builds a block diagonal matrix with the input parameters.
Bode diagram.
Computes a discrete-time state-space model from a continuous-time state-space model.
Solves the continuous-time Algebraic Riccati Equation.
Steady-state co-variance.
Controllability matrix.
Calculates the controllability staircase form.
Converts a discrete model to continuous time model.
Compute natural frequencies, damping ratios, and poles.
Solves the Discrete-time Algebraic Riccati Equations.
Transforms decibels (dB) to magnitude.
Low-frequency (DC) gain of a state-space or transfer function model
Linear-quadratic regulator for a discrete-time model.
Solve discrete-time Lyapunov or Sylvester equations.
Solves discrete-time Lyapunov equations with a square-root solver.
Constructs a descriptor state-space model.
Converts a descriptor state-space system into regular state-space form.
Extracts data from a descriptor state-space model.
Sorts continuous-time poles in descending order by the real component.
Returns the state estimator for a given estimator gain.
Compute the matrix exponential.
Constructs a transfer function model in DSP format.
Generates an input signal for the lsim function.
Computes the observability and controllability Gramians.
Computes the Hankel matrix.
Hankel singular values of a state-space or transfer function model.
Compute the impulse response of a control system.
Returns true if the LTI model is in continuous time.
Returns true if the state-space model is controllable.
Returns true if an LTI model is in discrete time.
Returns true if the state-space is observable.
Checks if an LTI model is single-input/single-output (SISO)
Checks if an LTI model is stable or unstable
Kalman filter or estimator.
Matrix logarithm.
Linear quadratic estimator (Kalman Filter)
Linear-quadratic regulator for a continuous-time model.
Calculates the optimal steady-state feedback gain matrix K.
Simulates LTI model response to arbitrary inputs.
Solves continuous Lyapunov or Sylvester equations.
Solves continuous-time Lyapunov equation using a square-root solver.
Computes magnitude from decibels (dB).
Minimal realization.
Nyquist diagram.
Returns the observability matrix of a state-space model.
Calculates the observability staircase form.
Computes the Pade approximation of time delays.
Connects two state-space or transfer functions in parallel.
Constructs a continuous-time PID controller transfer function.
Pole assignment.
Compute poles for a state-space or transfer function model.
Scale a state-space model.
Creates a state regulator with specified state-feedback and estimator gains.
Transforms a real Schur form to a complex Schur form.
Connects two state-space or transfer function in a series.
Matrix square root.
Constructs a state-space model.
Transforms a state-space model to another state-space model.
Converts state-space model parameters to transfer function model parameters.
Convert state-space model parameters to transfer function model parameters.
Extracts data from a state-space model.
Compute the step response of a control system.
Constructs a transfer function model
Transforms transfer function parameters to state-space parameters.
Transforms (continuous) transfer function parameters to zero-pole-gain parameters.
Transforms (discrete) transfer function parameters to zero-pole-gain parameters.
Extracts data from a transfer function model.
Zero-pole to state-space conversion.
Zero-pole to transfer function conversion.
Constructs a zero, pole, gain model.
Extracts data from a zero-pole-gain model.
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