Arduino PID Controller - From Scratch!

Summary

This video provides a hands-on introduction to PID (Proportional-Integral-Derivative) controllers using an Arduino. The presenter explains the basic principles of PID control, including proportional, integral, and derivative terms, and demonstrates how to implement them on a simple analog circuit. Viewers see the system in action, observing how the output responds to a setpoint, including overshoot, oscillations, and steady-state error. The video emphasizes practical experimentation, showing how adjusting gain values affects system behavior and encourages users to explore PID tuning themselves. It's a clear, accessible overview for anyone interested in learning feedback control through a tangible, real-world example.

Takeaways

• 😀 The video explains PID (Proportional-Integral-Derivative) controllers using a simple Arduino example.
• 😀 A feedback loop is created by connecting the Arduino's analog output through a filter back to its analog input.
• 😀 The Arduino code calculates the time delta (ΔT) for each loop iteration to accurately compute PID outputs.
• 😀 The error signal is the difference between the desired set point and the measured output, which drives the PID controller.
• 😀 The proportional (P) term scales output based on the current error to provide immediate correction.
• 😀 The integral (I) term accumulates the error over time to correct steady-state offsets.
• 😀 The derivative (D) term responds to the rate of change of the error to dampen oscillations.
• 😀 PID gains (KP, KI, KD) determine how much each term influences the output, and tuning these gains affects system stability and response.
• 😀 The system response typically shows overshoot, oscillation, and eventual settling toward the set point, representing a second-order response.
• 😀 Hands-on experimentation with gain values is recommended to build intuition on how PID controllers influence system behavior.
• 😀 Higher proportional gain increases response speed but can cause larger oscillations, while derivative gain helps stabilize sudden changes.
• 😀 The video encourages viewers to visualize the PID process using Arduino plotting tools and provides code and circuit diagrams on GitHub for practice.

Q & A

What is the purpose of a PID controller in a system?

A PID controller is designed to minimize the error between a setpoint and a system's output by continuously adjusting the output based on three factors: proportional, integral, and derivative gains. It aims to stabilize the system and maintain the target value over time.

Why does the PID controller cause the system to oscillate before settling?

The PID controller adjusts the system's output based on the error value. Initially, if the error is large, the controller responds with a significant change. However, this can cause the system to overshoot and oscillate. The controller then adjusts its output further to correct for the overshoot, leading to oscillations until it stabilizes.

What is meant by 'second-order system response' in control systems?

A second-order system response refers to the typical behavior of a system that exhibits oscillations before eventually stabilizing. It's often seen in systems controlled by PID controllers, where the response shows an overshoot, followed by oscillations that gradually decrease until the system reaches steady-state.

How do the PID gains affect the system's behavior?

The PID gains (proportional, integral, and derivative) control the system's response to error. The proportional gain determines how aggressively the system reacts to the current error, the integral gain corrects past errors, and the derivative gain anticipates future errors. Adjusting these values changes the response time, overshoot, and stability of the system.

What happens when the proportional gain is increased?

Increasing the proportional gain causes the system to react more strongly to the error, which can lead to faster responses but also greater overshooting and oscillation. If the gain is too high, the system may never settle and continue to oscillate.

How does a lower proportional gain impact the system's performance?

A lower proportional gain results in a slower response from the system. While this can reduce oscillations and overshooting, it may cause the system to take longer to reach the desired target value, leading to a less efficient response.

Why is the steady-state error in the system considered acceptable in this case?

The steady-state error in this case is small (oscillating between 74 and 76, which is a 2.7% error), which is considered acceptable for certain applications where a small error is tolerable. However, in more precision-demanding systems, a lower error might be required.

How can tuning the PID controller improve system performance?

Tuning the PID controller allows you to find the optimal balance between the three gains (proportional, integral, derivative) to minimize error and avoid overshooting or oscillations. Proper tuning ensures the system responds quickly, accurately, and stably to changes.

What is the role of the error signal in the PID controller?

The error signal represents the difference between the setpoint and the system's output. It is used by the PID controller to compute the necessary adjustments. As the system adjusts its output, the error signal decreases until it reaches a steady state, ideally close to zero.

What should you do if the PID controller leads to unacceptable oscillations or errors?

If the PID controller causes unacceptable oscillations or errors, the gains should be adjusted. Reducing the proportional gain can decrease oscillations, while increasing the integral or derivative gains may help improve stability and accuracy. Experimenting with different values can help find the right balance for the specific application.