Proportional-Integral-Derivative Controller Performance Assessment and Retuning Based on General Process Response...

Area of Science:

• Control Engineering
• Process Systems Engineering
• Industrial Automation

Background:

• Controller performance assessment is crucial for industrial processes.
• Traditional methods often require specific data types like step responses.
• Existing techniques may lack robustness for general process data.

Purpose of the Study:

• To review the current research status of controller performance assessment.
• To develop a generalized method for proportional-integral-derivative (PID) controller performance assessment.
• To enable effective controller retuning based on performance evaluation.

Main Methods:

• Utilizing signal integrals to make implicit model information explicit.
• Applying the least squares approach for low-order process model construction from response data.
• Employing a one-dimensional search algorithm for accurate process time delay estimation.
• Extending integral equation approaches for broader applicability to process responses.

Main Results:

• A detailed low-order process model is constructed using general response data.
• Performance benchmarks are established via simulated model output.
• The proposed method effectively identifies suboptimal controller performance using the Index of Absolute Integral Error (IAE).
• Appropriate retuning strategies are selected based on performance assessment.

Conclusions:

• The developed method provides a robust approach for PID controller performance assessment.
• Simulations and experimental results validate the effectiveness of the proposed technique.
• The study discusses critical aspects including time delay estimation, data preprocessing, and parameter selection for practical implementation.