- Start with the “Proportional (P)” gain: Set the “Integral (I)” and “Derivative (D)” gains to zero initially. Increase the “P” gain until the system starts to oscillate or exhibit sustained oscillations. This is known as the critical or ultimate gain.
- Determine the oscillation period: Measure the period of the oscillations, which is the time it takes for the system to complete one full cycle.
- Adjust the “Integral” and “Derivative” gains: Once the “P” gain is set, you can fine-tune the “I” and “D” gains. The “I” gain helps eliminate steady-state errors, while the “D” gain reduces the overshoot and improves response time.
- Test and iterate: Test the system's response to the changes in gains and observe its behavior. If necessary, adjust the gains further based on the system's performance. Iterate this process until you achieve the desired response.
Genetic algorithm for FOPID in simulink
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cam anyone please help me tune the gai paramters of fractional order PID controller in simulink.
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Gagan Agarwal
2023 年 8 月 31 日
Hi Md Muzakkir Quamar
To optimize the gain parameters of your PID controller, you can proceed with the following standard steps:
It is also worth considering advanced tuning methods like Ziegler-Nichols, Cohen-Coon etc.
You can also refer to the link below to know how to adjust the above-mentioned parameters in Simulink: -
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Sam Chak
2023 年 8 月 31 日
Hi @Gagan Agarwal, those steps do not seem to optimize the gain parameters of your PID controller. The steps also do not mention the Integral Time Absolute Error (ITAE) performance cost function. Which optimal control textbooks are you referring to?
Moreover, @Md Muzakkir Quamar asked about tuning the gains of the fractional-order PID control using the genetic algorithm. None of the steps mention the fractional parameters λ and μ. Could you provide a simple example of optimizing the FOPID controller for a Double Integrator, ?
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