A control systems design toolbox for Julia.
To install, in the Julia REPL:
using Pkg; Pkg.add("ControlSystems")
c2d(::StateSpace)
now returns only the system, not the x0map
. See c2d_x0map
for the old functionality.baltrunc
.c2d
. We now support :zoh,:foh,:fwdeuler,:tustin
More details under releases.
lsimplot, stepplot, impulseplot
now have the same signatures as the corresponding non-plotting function.d2c
for conversion from discrete to continuous.Release v0.7 introduces a new TimeEvolution
type to handle Discrete/Continuous
systems. See the release notes.
sys = tf(1, [1,1])*delay(1)
stepplot(sys, 5) # Compilation time might be long for first simulation
nyquistplot(sys)
New state-space type HeteroStateSpace
that accepts matrices of heterogeneous types: example using StaticArrays
.
All functions have docstrings, which can be viewed from the REPL, using for example ?tf
.
A documentation website is available at http://juliacontrol.github.io/ControlSystems.jl/latest/.
Some of the available commands are:
ss, tf, zpk
pole, tzero, norm, hinfnorm, linfnorm, ctrb, obsv, gangoffour, margin, markovparam, damp, dampreport, zpkdata, dcgain, covar, gram, sigma, sisomargin
care, dare, dlyap, lqr, dlqr, place, leadlink, laglink, leadlinkat, rstd, rstc, dab, balreal, baltrunc
pid, stabregionPID, loopshapingPI, pidplots
step, impulse, lsim, freqresp, evalfr, bode, nyquist
lsimplot, stepplot, impulseplot, bodeplot, nyquistplot, sigmaplot, marginplot, gangoffourplot, pidplots, pzmap, nicholsplot, pidplots, rlocus, leadlinkcurve
minreal, sminreal, c2d
This toolbox works similar to that of other major computer-aided control systems design (CACSD) toolboxes. Systems can be created in either a transfer function or a state space representation. These systems can then be combined into larger architectures, simulated in both time and frequency domain, and analyzed for stability/performance properties.
Here we create a simple position controller for an electric motor with an inertial load.
using ControlSystems
# Motor parameters
J = 2.0
b = 0.04
K = 1.0
R = 0.08
L = 1e-4
# Create the model transfer function
s = tf("s")
P = K/(s*((J*s + b)*(L*s + R) + K^2))
# This generates the system
# TransferFunction:
# 1.0
# ---------------------------------
# 0.0002s^3 + 0.160004s^2 + 1.0032s
#
#Continuous-time transfer function model
# Create an array of closed loop systems for different values of Kp
CLs = TransferFunction[kp*P/(1 + kp*P) for kp = [1, 5, 15]];
# Plot the step response of the controllers
# Any keyword arguments supported in Plots.jl can be supplied
stepplot(CLs, label=["Kp = 1" "Kp = 5" "Kp = 15"])
See the examples folder and ControlExamples.jl