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Understanding PID Control: 2-DOF Ball Balancer Experiments

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Understanding PID Control: 2-DOF Ball Balancer Experiments: QuakeLogic engineering guidance on engineering education and robotics, applications, data quali...

This article explains how to use PID controllers to solve a real-world balance problem. We need to calculate PID gains to do so. Let’s start first with the Ziegler-Nichols method:

Ziegler-Nichols Method

Ziegler-Nichols method is very useful for calculating the controller gains. This method begins by zeroing the integral and differential gains. After this step, the proportional gain is increased until the system oscillates. After finding the proportional gain that makes the system oscillate, the other gains of the controller are calculated with the help of the table below.

Ziegler-Nichols Method table
Figure 1: Ziegler-Nichols Method



To use this method, you can follow the steps below:

Engineering visual for Understanding PID Control: 2-DOF Ball Balancer Experiments
Figure 2: (Algorithm to calculate the PID gains using the Ziegler-Nichols method


Damping

In the real world, friction affects the behavior of the systems. If there were no frictions, the systems wouldn’t stop and oscillations would continue indefinitely.

Engineering visual for Understanding PID Control: 2-DOF Ball Balancer Experiments
Figure 3: The balls would keep hitting forever if there weren’t any friction (even though the video loops)

If friction becomes zero, some systems can behave infinitely like Figure 3.

If the damping ratio gets close to zero, the system will spend more time stopping. If the system can’t stop, it is called oscillation. In the oscillation, the system moves between some of the points. The step response is a commonly used method to analyze systems’ behavior. The system’s behavior can be followed by a step response. In figure 4, we can easily see the relevance between the damping ratio and system behavior. For example, the system can directly reach the set point when ζ=1 however if  ζ=0, the system can’t stop and reach the set point.

We can classify the damping ratio for its oscillation types. We can show the damping ratio with the ζ (Tau) symbol and it is classified as follows:

  • ζ<1 The system is underdamped
  • ζ>1 The system is overdamped
  • ζ=1 The system is critically damped

We can easily understand what the damping ratio means in real life using Acrome’s Ball Balancing Table. The animations below show different damping ratios which are changed using the controller’s PID parameters.

Engineering visual for Understanding PID Control: 2-DOF Ball Balancer Experiments
Figure 4: Critically damped PID controller exercise using Ball Balancing Table

In figure 4, the ball movement shows a critically damped behavior. It can reach to set point fastly with zero error. We can consider that the ball’s ζ is close to 1.

Engineering visual for Understanding PID Control: 2-DOF Ball Balancer Experiments
Figure 5: Underdamped PID controller exercise using Ball Balancing Table

Engineering visual for Understanding PID Control: 2-DOF Ball Balancer Experiments
Figure 6: Overdamped PID controller exercise using Ball Balancing Table

In Figure 6, the ball behaves overdamped. It reaches a set point slowly, which means the ζ>1.

Engineering visual for Understanding PID Control: 2-DOF Ball Balancer Experiments
Figure 7: Unstable PID controller exercise using Ball Balancing Table

In Figure 7, the ball behaves in unstable behavior. It can’t reach the set point. Also, the ball draws a random direction on the table

Engineering visual for Understanding PID Control: 2-DOF Ball Balancer Experiments
Figure 8: Step response of the 3 different step response types.

Balancing is a very common problem in the industry. Some of the systems are affected by balance. So the system’s balance should be under control. For example, planes can change direction by balance. Moreover, you have already seen in MotoGP™ riders change motorbikes’ slopes instead of turning the handlebar for changing direction.

Engineering visual for Understanding PID Control: 2-DOF Ball Balancer Experiments
Figure 9: MotoGP™ is a place where vehicle dynamics + driver abilities combine with each other for controlling the balance of the motorbike.

One Dimensional Balance Problem

Aircraft Roll Motion can also be considered as another real-life example of a balancing problem.

Engineering visual for Understanding PID Control: 2-DOF Ball Balancer Experiments
Figure 10 – Roll Motion of the Aircraft. Similar to BBT’s counter motor action, a counter aileron movement is required to control the rolling action.

Rotation around the front to the back axis is called roll. On the outside of a wing, there are small hinged portions called ailerons. An airplane can produce a rolling motion by using its ailerons. Ailerons usually work in opposite positions. For both wings, the lift force (Fr or Fl) of the wing section through the aileron is applied at the section’s aerodynamic center, which is some distance (L) from the aircraft’s center of gravity. This creates a torque T=F x L

Engineering visual for Understanding PID Control: 2-DOF Ball Balancer Experiments
Figure 11: Force vectors, CoG, and Resulting Motion happening during the aircraft’s roll motion.

If the ailerons are not controlled correctly, the aircraft will move undesirably. It is exactly what happens in a 1-D ball-balancing application. It can be simulated in a controlled lab using experiment systems such as ACROME’s Ball and Beam System. The Ball and Beam System is one of the real-life applications of the rolling event. Students can experiment with this 1-D balancing application and work with the PID controllers to understand the effect of the ailerons.

Engineering visual for Understanding PID Control: 2-DOF Ball Balancer Experiments
Figure 12: ACROME’s Ball and Beam


You can watch using the Ball and Beam Video

You can read more on how Ball and Beam works.

Two Dimensional Balance Problem

The Acrome Ball balancing table is a good experiment for 2-D PID control.

acrome Ball Balancing Table
Figure 13: Unlike Ball and Beam, the Ball Balancing Table controls the position of the ball in 2 dimensions.

Now let’s focus on another angle of control of the airplanes: The Pitch angle. The pitch angle of the planes can be controlled by another wing set called the Elevator. Similar to the ailerons, the elevator is also controlled (up and down) to control the pitch angle of the airplanes.

Engineering visual for Understanding PID Control: 2-DOF Ball Balancer Experiments
Figure 14 – The elevator is used to control the pitch (the nose) angle of the airplanes.

This is analogous to controlling the ball with 2 servo motors. How can we do that? 

One of the motors can  control x dimension and the other motor control y dimension.Each motor has different PID controlersl so one motor can only control one dimension.

pitch and roll of the Acrome Ball Balancing Table’s top plate
Figure 15: The two servo motors are used to control the pitch and roll angles of the Ball Balancing Table’s top plate.

You can read more on how the Ball Balancing Table is working.

This concludes our blog about the PID controller. We hope you enjoyed this document.

Feel free to contact us with your questions or recommendations about the PID controllers.

Last reviewed: 2026-07-04

Executive Summary

Engineering education and robotics systems help students and researchers connect control theory, sensing, actuation, software, and real-time experimentation. This article is maintained as a QuakeLogic engineering resource for readers evaluating terminology, applications, instrumentation, and practical implementation considerations. The content is educational and should be reviewed against project-specific requirements, applicable standards, manufacturer documentation, and qualified engineering judgment.

Key Takeaways

  • Start with the engineering objective, operating environment, required measurements, and decision workflow.
  • Use calibrated instrumentation, documented configuration, appropriate sampling, and traceable data handling where results support engineering decisions.
  • Interpret results in context; boundary conditions, installation quality, noise, bandwidth, and site conditions can materially affect conclusions.
  • Use standards and references as guidance, not as substitutes for project-specific engineering review.

Technical Explanation

A credible engineering workflow links the physical system, the measurement chain, data acquisition, processing, interpretation, and reporting. For testing, that means documenting the input, payload, fixture, limits, safety controls, and acceptance criteria. For monitoring, that means documenting sensor type, placement, orientation, coupling, timing, communications, maintenance, alarm logic, and review procedures.

Engineering Applications

Use CasePrimary QuestionUseful Documentation
Research or educationWhat behavior can be measured, demonstrated, or repeated?Test plan, configuration notes, input data, calibration records, and observations.
Infrastructure or facility monitoringIs response normal, changing, or outside expected limits?Baseline data, event records, thresholds, inspection notes, and engineering review.
Product or system selectionWhich specifications matter for the application?Measurement range, bandwidth, accuracy, environment, integration needs, and deliverables.

People Also Ask

What information should be gathered before selecting equipment?

Define the measurement objective, expected amplitude and frequency range, installation environment, data format, timing requirements, communications, reporting needs, and applicable standards.

How can data quality be protected?

Use appropriate sensor mounting, calibration, channel naming, time synchronization, clipping checks, noise review, and documented maintenance procedures.

When is human engineering review required?

Human review is required when results affect safety, compliance, operations, procurement, structural assessment, or emergency response decisions.

Related Technologies and Resources

References

Recommended Media

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QuakeLogic supports seismic monitoring, earthquake early warning, structural health monitoring, infrasound monitoring, vibration monitoring, data acquisition, robotics education, and shake table testing workflows. For project-specific guidance, contact QuakeLogic with the application, measurement objective, environment, and required deliverables.


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Published by QuakeLogic engineers and seismic monitoring specialists. QuakeLogic designs earthquake early warning, structural health monitoring, infrasound, vibration monitoring, and shake table testing systems for infrastructure, research, public safety, and industrial engineering teams.

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Related engineering knowledge areas

Definitions and references

Terms, standards, and source cues

  • SHM: related to Structural Health Monitoring in this QuakeLogic knowledge cluster.
  • damage detection: related to Structural Health Monitoring in this QuakeLogic knowledge cluster.
  • earthquake early warning: related to Earthquake Early Warning in this QuakeLogic knowledge cluster.
  • seismic switch: related to Earthquake Early Warning in this QuakeLogic knowledge cluster.
  • infrasound sensors: related to Infrasound Monitoring in this QuakeLogic knowledge cluster.
  • low-frequency noise: related to Infrasound Monitoring in this QuakeLogic knowledge cluster.
  • shake tables: related to Shake Tables in this QuakeLogic knowledge cluster.
  • AC156: related to Shake Tables in this QuakeLogic knowledge cluster.

Standards mentioned

  • ISO documentation only when supported by source material

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