Controlling industrial dead-time systems: When to use a PID or an advanced controller

Area of Science:

• Process Control
• Control Engineering
• Industrial Automation

Background:

• Industrial processes often feature dead time, noisy measurements, and modeling errors, complicating control system design.
• Traditional Proportional-Integral-Derivative (PID) controllers are widely used but may face limitations in performance for complex dynamics.
• More advanced strategies like Direct Torque Control (DTC) and Model Predictive Control (MPC) offer potential improvements but require more complex implementation.

Purpose of the Study:

• To conduct a comparative analysis of PID, DTC, and MPC control strategies.
• To evaluate their performance in Single-Input Single-Output (SISO) processes with dead time, considering industrial constraints.
• To assess the impact of noisy measurements and modeling errors on control strategy effectiveness.

Main Methods:

• Comparative analysis of PID, DTC, and MPC control algorithms.
• Simulation of SISO processes with dead time under various conditions, including noise and model uncertainty.
• Evaluation of controller performance based on criteria such as robustness, speed of response, and disturbance rejection.

Main Results:

• For unconstrained processes requiring high robustness, advanced strategies offer little to no performance improvement over PID.
• For processes with well-defined models, even small dead times justify the use of more complex control structures like DTC or MPC.
• For constrained processes, PID controllers with anti-windup mechanisms can achieve performance comparable or superior to MPC, especially when robustness is prioritized.

Conclusions:

• The choice of control strategy depends critically on process characteristics, including model accuracy, constraints, and robustness requirements.
• PID controllers, particularly with anti-windup, remain a competitive and effective solution for many industrial control problems, even when compared to advanced methods.
• Advanced control strategies like DTC and MPC demonstrate value in specific scenarios, such as well-modeled processes or when precise trajectory tracking is essential.