Auberin Auto Tune Pid Controller

 admin

This example shows how to automatically tune a PID Controller block using PID Tuner.

The process of finding these values is referred to as “tuning.” When a PID controller is tuned optimally, the device minimizes deviation from the set point, and responds to disturbances or set point changes quickly but with minimal overshoot. This White Paper from OMEGA.

Autotuning PID Controllers (PID and Fuzzy Logic Toolkit). How-To: Programmatically Autotuning a Previously Implemented PID Controller; PID Online Autotuning VI: Generating PID parameters for a system given an input/output signal. This technique is useful when you have insufficient information about the system and you want to develop initial. When i want to autotune PID parameters in a closedloop control system that it's Plant is an ADAMS/viwe plant, I have a problem: linearization failed: The plant model in the PID loop linearizes to zero, and therefore cannot be used in PID controller design. Jun 14, 2015  Set up your Bradley to do a cook. Set the time and temp you want on the PID. I would recommend that you cook something that takes a while so the PID has time to complete the autotune which could take a while. Press the set key and hold it until 'LCK' displays. Now press the '+' key until it gets to the number '166' then press set. Mar 06, 2018  PID Temperature Control Controller for SSR, w/Dual Alarm, SYL-2352. But it also has an auto tune function so pid setup would be quick and easy. In my application I can’t allow the temperature to drift so it can run the calculations by itself due to the fact I’m using it for a fish tank. Learn about PID controller tuning and how to adjust PID controller settings. Information about the Basics of PID control and various types of PID tuning. While most modern controllers provide auto tune capabilities, it is still important to understand how to tune a PID controller.

Introduction of the PID Tuner

PID Tuner provides a fast and widely applicable single-loop PID tuning method for the Simulink® PID Controller blocks. With this method, you can tune PID controller parameters to achieve a robust design with the desired response time.

A typical design workflow with the PID Tuner involves the following tasks:

(1) Launch the PID Tuner. When launching, the software automatically computes a linear plant model from the Simulink model and designs an initial controller.

(2) Tune the controller in the PID Tuner by manually adjusting design criteria in two design modes. The tuner computes PID parameters that robustly stabilize the system.

(3) Export the parameters of the designed controller back to the PID Controller block and verify controller performance in Simulink.

Open the Model

Open the engine speed control model with PID Controller block and take a few moments to explore it. Dev c c99 mode.

Design Overview

In this example, you design a PI controller in an engine speed control loop. The goal of the design is to track the reference signal from a Simulink step block scdspeedctrlpidblock/Speed Reference. The design requirement are:

  • Settling time under 5 seconds

  • Zero steady-state error to the step reference input.

In this example, you stabilize the feedback loop and achieve good reference tracking performance by designing the PI controller scdspeedctrl/PID Controller in the PID Tuner.

Open PID Tuner

To launch the PID Tuner, double-click the PID Controller block to open its block dialog. In the Main tab, click Tune.

Initial PID Design

When the PID Tuner launches, the software computes a linearized plant model seen by the controller. The software automatically identifies the plant input and output, and uses the current operating point for the linearization. The plant can have any order and can have time delays.

The PID Tuner computes an initial PI controller to achieve a reasonable tradeoff between performance and robustness. By default, step reference tracking performance displays in the plot.

The following figure shows the PID Tuner dialog with the initial design:

Display PID Parameters

Click Show parameters to view controller parameters P and I, and a set of performance and robustness measurements. In this example, the initial PI controller design gives a settling time of 2 seconds, which meets the requirement.

Adjust PID Design in PID Tuner

The overshoot of the reference tracking response is about 7.5 percent. Since we still have some room before reaching the settling time limit, you could reduce the overshoot by increasing the response time. Move the response time slider to the left to increase the closed loop response time. Notice that when you adjust response time, the response plot and the controller parameters and performance measurements update.

The following figure shows an adjusted PID design with an overshoot of zero and a settling time of 4 seconds. The designed controller effectively becomes an integral-only controller.

Complete PID Design with Performance Trade-Off

Antares Auto-tune

In order to achieve zero overshoot while reducing the settling time below 2 seconds, you need to take advantage of both sliders. You need to make control response faster to reduce the settling time and increase the robustness to reduce the overshoot. For example, you can reduce the response time from 3.4 to 1.5 seconds and increase robustness from 0.6 to 0.72.

The following figure shows the closed-loop response with these settings:

Write Tuned Parameters to PID Controller Block

After you are happy with the controller performance on the linear plant model, you can test the design on the nonlinear model. To do this, click Update Block in the PID Tuner. This action writes the parameters back to the PID Controller block in the Simulink model.

The following figure shows the updated PID Controller block dialog:

Completed Design

The following figure shows the response of the closed-loop system:

The response shows that the new controller meets all the design requirements.

You can also use the Control System Designer to design the PID Controller block, when the PID Controller block belongs to a multi-loop design task. See the example Single Loop Feedback/Prefilter Compensator Design.

Auburn Auto Tune Pid Controller Download

See Also

Related Topics

A self-tuning PID demonstration GPL software using genetic algorithm.

Demonstration video here : https://www.youtube.com/watch?v=cK6kWN9K_do

Explanation here : https://kevinjoly25.wordpress.com/2015/01/13/pid-controller-auto-tuning-using-genetic-algorithm/

  • Qt4

$ mkdir build
$ cd build
$ cmake .
$ make

No install method has been provided yet. However, you can run the software from the build directory:$ ./pid-autotune

There is 4 dock widgets in this software:

  • Motor: enable the user to choose a motor to use and test it in closed on opened loop.
  • Controller : enable the user to choose a controller to use with the motor (check 'Use controller'). The controller parameters can be set in this widget for test purpose.
  • Graph settings : enable the user to change the axes scale by setting the min and max to be displayed.
  • Genetic : enable the user to control the genetic algorithm parameters such as:
    • input : value of the input applied on the system.
    • min/max Kx : boundary values of each PID action.
    • Evaluation time : system running time when evaluating fitness.
    • Population size : size of the genetic algorithm's population.
    • Mutation ratio : probability to mutate the offspring's variable.
    • Crossover ratio : probability to crossover two parents.
    • Overshoot penalty : ratio which multiply the error when an overshoot occurs. If you don't want any overshoot, set this to the maximum.
    • Elite num : Number of best parents kept in the next generation of population.The start button launch the genetic process. Pause stop the process, press start to launch it again without any loss. Reset enable the user to generate a new random population by deleting the old one.

Example

  • Under 'Motor' : choose the DummyMotor.
  • Under 'Graph settings' : set xMax to 0.1 and yMax to 2.0.
  • Under 'Genetic' : set maxKp to 1.0, maxKd to 2.0, maxKi to 0.1.
  • Hit start button and enjoy the dance of a self-tuning PID! ;)

Auburn Auto Tune Pid Controller For Sale

More on GAs..

Auburn Auto Tune Pid Controller Download

The fitness function is using the sum of squarred error to evaluate the generated PID.Thanks to this fitness function, tournament selection can be used in order to select parents of the next PID population.The genetic algorithm implemented in Genetic.cpp uses arithmetic crossover and gaussian mutation to generate the new population.Elitism can be used.

Auburn Auto Tune Pid Controller For Sale

This software is using the GPL software QCustomPlot from Emanuel Eichhammer.