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Control System Toolbox lets you easily tune PID controller gains. If you have a plant model,
you can launch a PID Tuner app for this plant model.
When it opens up, it automatically tunes PID gains for you to achieve the right balance of performance and robustness.
You can quickly try different controller types
such as proportional only, proportional-integral, and PID. You can inspect the tuned PID gains
as well as performance and robustness characteristics such as rise time,
settling time, overshoot, gain margin and phase margin.
You can use the interactive sliders to adjust system performance. You can adjust the response time
with the first slider and the phase margin with the second one.
In addition to the step response plot, you can also look at the bode plot of your system. You can also look at different responses.
By default, PID Tuner app shows you the reference tracking response,
but you can choose to look at other responses such as controller effort and input and output disturbance rejection.
You can look at several plots simultaneously. Using these responses you can adjust controller performance
for optimal setpoint tracking or disturbance rejection results.
Once you are satisfied with the design, you can export the PID controller into MATLAB where it will be represented as a PID object.
In addition to the PID Tuner App, Control System Toolbox also provides a function with the same functionality for tuning PID gains.
{\rtf1This function is called \b \i pidtune\b0\i0\b . Y\b0ou can call this function with a plant model as an input argument to design a default PID controller}
or you can also specify desired gain crossover frequency. The output of the function is the tuned PID controller represented
by a PID object. Once you have a PID object in MATLAB workspace, you can easily access and if needed modify individual gains.
You can use PID object like any other LTI model. For example, you can compute closed loop
transfer function and plot its step response. This concludes the video.