In industrial automation, the task of tuning PID controllers is often performed by a single experienced engineer within a team. This pattern persists regardless of the industry or the size of the department.
The process involves adjusting three parameters and observing the system's reaction. However, the primary challenge lies in decision-making after applying changes, such as determining whether to wait or switch to manual mode.
Many engineers mistakenly believe that any issue can be resolved by finding the right combination of coefficients. In reality, problems often stem from mechanical issues, sensor errors, or process limitations rather than the controller itself.
Experienced engineers distinguish themselves by recognizing when a PID controller has reached its limit, allowing them to shift focus to diagnosing hardware or process faults.
To help engineers gain experience without risking real equipment, the platform PIDLAB.io was created. It provides models of typical scenarios for training and decision-making practice.
