Control System functions

The Control System module provides algorithms and tools for designing, analyzing, and tuning linear control systems in Nelson.

It supports state-space and transfer function models, system transformations between continuous and discrete time, and computation of poles, zeros, and frequency responses.

The module also includes functionality for system balancing, controllability and observability analysis, regulator and estimator design, and simulation of dynamic system responses.

These tools enable robust modeling, analysis, and control of linear dynamic systems for engineering and research applications.

abcdchk
Verifies the dimensional compatibility of matrices A, B, C, and D.
acker
Pole placement gain selection using Ackermann's formula.
append
Appends the inputs and outputs of the two models.
augstate
Append state vector to output vector.
balreal
Gramian-based balancing of state-space realizations.
bdschur
Block-diagonal Schur factorization.
bode
Bode plot of frequency response, magnitude and phase data.
c2d
Convert model from continuous to discrete time.
care
Continuous-time algebraic Riccati equation solution.
cloop
Feedback connection of multiple models.
compreal
Companion realization of transfer functions.
ctrb
Controllability of state-space model.
ctrbf
Compute controllability staircase form.
d2c
Convert model from discrete to continuous time.
damp
Natural frequency and damping ratio.
dare
Discret-time algebraic Riccati equation solution.
dcgain
Low-frequency (DC) gain of LTI system.
dlqr
Linear-quadratic (LQ) state-feedback regulator for discrete-time state-space system.
dlyap
Discrete-time Lyapunov equations.
dsort
Sort discrete-time poles by magnitude.
esort
Sort continuous-time poles by real part.
evalfr
Evaluate frequency response at given frequency.
feedback
Feedback connection of multiple models.
freqresp
Evaluate system response over a grid of frequencies.
gensig
Create periodic signals for simulating system response.
gram
Controllability and observability Gramians.
hsvd
Hankel singular values of dynamic system.
impulse
Impulse response plot of dynamic system.
initial
System response to initial states of state-space model.
isct
Checks if dynamic system model is in continuous time.
isdt
Checks if dynamic system model is in discret time.
islti
Checks if variable is an linear model tf, ss or zpk.
issiso
Checks if dynamic system model is single input and single output.
isstatic
Checks if model is static or dynamic.
kalman
Design Kalman filter for state estimation.
lqe
Kalman estimator design for continuous-time systems.
lqed
Calculates the discrete Kalman estimator configuration based on a continuous cost function.
lqr
Linear-Quadratic Regulator (LQR) design.
lqry
Form linear-quadratic (LQ) state-feedback regulator with output weighting.
lsim
Plot simulated time response of dynamic system to arbitrary inputs.
lyap
Continuous Lyapunov equation solution.
minreal
Minimal realization or pole-zero cancellation.
nyquist
Nyquist plot of frequency response.
obsv
Observability of state-space model.
obsvf
Compute observability staircase form.
ord2
Generate continuous second-order systems.
padecoef
Computes the Pade approximation of time delays.
parallel
Parallel connection of two models.
pole
Poles of dynamic system.
series
Series connection of two models.
ss
State-space model.
ss2tf
Convert state-space representation to transfer function.
ssdata
Access state-space model data.
ssdelete
Remove inputs, outputs and states from state-space system.
ssselect
Extract subsystem from larger system.
step
Step response plot of dynamic system.
tf
Constructs a transfer function model.
tf2ss
Convert transfer function filter parameters to state-space form.
tfdata
Access transfer function model data.
tzero
Invariant zeros of linear system.
zero
Zeros and gain of SISO dynamic system.