This is the table of contents, arranged by topic.

If you are looking for the use of a particular function, try the Function index.

There is also a set of YouTube videos linked to the course.

The tbcontrol module contains functions helpful to students learning to solve control problems. It is broken up into submodules.

`linearise`

attempt to linearise a symbolic expression`routh`

construct a Routh-Hurwitz array`pade`

pade approximation`ss2tf`

determine the transfer function version of a state space realisation`sampledvalues`

invert the Z transform symbolically`evaluate_at_times`

evaluate a sympy expression at numeric times (useful for plotting responses)

`skogestad_half`

find an approximation of a high order system by Skogestad's half rule

`cross_axis`

create an axis in Matplotlib which has spines going through the origin like a Nyquist diagram would

`feedback`

calculate the result of having two blocks in a feedback loop

Step responses of certain systems

`fopdt`

first order plus dead time`sopdt`

second order plus dead time

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