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PID Controller Implementation in Software และรูปภาพที่เกี่ยวข้องsoftware หมายถึง

PID Controller Implementation in Software
PID Controller Implementation in Software

software หมายถึง และข้อมูลที่เกี่ยวข้อง

Mã nguồn có sẵn tại đây: Cách triển khai bộ điều khiển PID trong phần mềm sử dụng C, thảo luận về lý thuyết và các cân nhắc thực tế. Trình diễn mã bộ điều khiển PID sử dụng trình mô phỏng chuyến bay tùy chỉnh. Nếu bạn thích nội dung của tôi, vui lòng cân nhắc trở thành khách quen:

[NOTE] Một cái gì đó tôi quên đề cập đến trong video! Lưu ý về ‘đạo hàm trên phép đo’: Vì ‘tín hiệu lỗi’ đi vào bộ phân biệt hiệu quả không phụ thuộc vào điểm đặt: e[n] = 0 – phép đo, và do đó (e[n] – e[n – 1]) = (0 – đo lường) – (0 – đo lường trước) = -Kd * (đo lường – đo lường trước). Lưu ý dấu trừ so với đạo hàm trên lỗi! Tôi đã thực hiện thay đổi trong repo Git – trước khi bạn phải sử dụng độ lợi Kd âm để có được kết quả tương tự. Bây giờ bạn có thể, như bình thường với đạo hàm trên lỗi, sử dụng độ lợi Kd dương như bình thường. Lưu ý thêm: Bộ lọc thông thấp dẫn xuất có thể được điều khiển bởi hằng số ‘tau’, là hằng số thời gian của bộ lọc (tần số -3dB tính bằng Hz, fc = 1 / (2 * pi * tau)). Giá trị tau lớn hơn có nghĩa là tín hiệu được lọc nhiều hơn. Khi tau tiến gần đến 0, bộ phân biệt tiến tới ‘bộ phân biệt thuần túy’ mà không cần lọc.

[TIMESTAMPS] 00:00 Giới thiệu 00:39 Khái niệm cơ bản về hệ thống điều khiển 02:40 Biểu diễn PID trong miền liên tục 04:57 Chuyển đổi từ miền liên tục sang miền rời rạc 06:11 Phương trình chênh lệch bộ điều khiển PID 07:35 Cân nhắc thực tế 10:48 Cấu trúc phần mềm cơ bản 11:53 Triển khai trong C 18:46 Ví dụ: Trình mô phỏng bay sử dụng mã bộ điều khiển PID

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43 Comments

  1. Something I forgot to mention in the video! Note on 'derivative-on-measurement': Since the 'error signal' effectively going into the differentiator does not depend on the setpoint: e[n] = 0 – measurement, and therefore (e[n] – e[n – 1]) = (0 – measurement) – (0 – prevMeasurement) = -Kd * (measurement – prevMeasurement). Note the minus sign compared to derivative-on-error!
    I've made the change in the Git repo – before you would have had to use a negative Kd gain to get the same result. Now you can, as normal with derivative-on-error, use a positive Kd gain as usual.

  2. As a fellow lover of microcontrollers and Signal Processing I absolutely love the content on this channel… I have to say that Phil does a great job of getting through the rather advanced mathematics and focuses on only the essentials. Great work.

  3. Thank you for the really well explained tutorial especially the implementation in the code. I was searching for something like this. This is exactly what I was looking for! Many thanks on your really awesome video!

  4. Thank you, I am going to use this for my antenna rotor controller that has phi and theta to track satellites. Me and my dad are currently trying to contact the International Space Station using the rotor controller!

  5. all that good explanation was completely ruined when you glazed over the Derivative formula, completely ignoring where or how you came up with the "tau" parameter. It is unclear what that represents in terms of Code.

  6. thanks very much for this tutorial. Could you please explain the difference between T and tau. Sampling time vs Time constant for the filter? Where do we get its value from? How do we use this: (-3dB frequency in Hz, fc = 1 / (2*pi*tau))?

  7. Thanks for the useful Video, I decided to implement your PID algorithm to Temperature control of 1000 degrees furnace and wondering how to determine TAU and sample time. Note that my microcontroller will generate 2 seconds PWM (slow PWM) and I will control the temperature through Duty Cycle. regards

  8. Majestic work. Can you please write and explain code for other controllers, such as, Adaptive controller. I can help you providing related materials and explanation if you want.

  9. Is there any guidance of the integrator limits in relation to the output limits ? I want to use this in a motor control application, where my rotation sensors report between 0-200, and can control rpm of motor between 0-100. Btw, this channel is awesome. I've built a number of PCBs based on the guidance you've provided – all worked first time :)

  10. @Phil's Lab Thank you for the video it was very useful software wise but when it came to the mathematical reasoning I didn't understand anything(I'm a Sophomore in High School). I've been trying to find a video that emphasises on the mathematical reasoning so I can be absolutely certain that this code will work. But I haven't found any that explains it on my level. If there is a video or any kind of website that explains this on a basic level, I would really appreciate it if someone could share the link.

  11. Thanks for your PID lecture and code. Does this solution work in any application? I plan to use your PID code to control the pressure. My system is the Pressure Valve that can be controlled by input in mA (4mA-20mA range: 4mA ~ 0Pa, 20mA – 100Bar). If my desired pressure Bar is 75 Bar I would need to adjust my PLC output in mA current until my error is zero (desired pressure – measured pressured at sensor). Can you provide C# code for your simulator? Thanks a lot

  12. I want to design a pid controller for my scientific equipment stability chamber of temperature, humidity, light controller.

    Could you guide me sir as I am beginer, I purchase pid controller but I eager to make my self.

  13. I have a question regarding the use of the PID controller. For example, you have to balance a bar at a set angle with two motors on the ends (something like half of a quadcopter).

    The measurement is the current angle or the angular rate of the system.

    The input into the plant is some sort of number for example from 125-250 (min to max throttle).

    My question is – what kind of unit does the PID controller work in and how is the unit selected?

    On one hand, it's good for it to work with the input from the gyro since that's how the system determines the error between the desired angle and the current angle, but on the other hand, its good for it to work with the throttle value, because that's what the PID is supposed to output.

  14. By far one of the best YouTubers at explaining both hardware and software. Clearly very knowledgeable, I am currently consuming your content as fast as possible

  15. Great video pal! I can't find the link for the dynamic integrator clamping method that you mentioned in the video anywhere in the description :/
    Could you maybe upload it here in the comments section?
    Cheers

  16. In the video you say that the material from which the tustin discretization is done should be linked. I cannot find it, so could you link it either in the desciption or as a comment to this comment?
    Otherwise, really nice video :)

  17. What does PID stand for? This:

    A proportional–integral–derivative controller (PID controller or three-term controller) is a control loop mechanism employing feedback that is widely used in industrial control systems and a variety of other applications requiring continuously modulated control. A PID controller continuously calculates an error value e(t) as the difference between a desired setpoint (SP) and a measured process variable (PV) and applies a correction based on proportional, integral, and derivative terms (denoted P, I, and D respectively), hence the name. -wiki

  18. Thank you very much for your videos, you are a beast!! Please DO NOT STOP (EVER) and excuse my stupidity but i have to ask.
    I tested your code and of course it works perfectly, but I would like to understand why (when you simulate the first order system update) the output of the plant is:
    output = (SAMPLE_TIME_S * inp + output) / (1.0f + alpha * SAMPLE_TIME_S);
    I'm not grasping that and it's haunting me.

    Much love from Spain ^^

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