Optimized robust control for industrial unstable process via the mirror-mapping method.

Area of Science:

• Control Engineering
• Process Systems Engineering
• Industrial Automation

Background:

• Industrial processes often exhibit instability and time delays, posing significant control challenges.
• Existing robust control methods may struggle with stringent stability constraints for such systems.
• Minimizing sensitivity is crucial for enhancing robustness in complex industrial control applications.

Purpose of the Study:

• To propose a novel optimized robust control algorithm for unstable industrial processes with time delay.
• To enhance system robustness by minimizing the sensitivity function.
• To develop a systematic methodology for controller design and stability analysis.

Main Methods:

• The study employs a mirror-mapping method for controller design.
• Padé approximation is used to transform the unstable system into a stable form for controller synthesis.
• A graphical stability criterion is utilized to determine the exact stabilizing region.
• The design parameter is linked to the closed-loop system's stability degree.

Main Results:

• The proposed algorithm effectively handles unstable plants by releasing internal stability constraints.
• A systematic methodology provides an exact stabilizing region based on a single design parameter.
• Experimental validation demonstrates satisfactory performance in disturbance rejection and robustness.

Conclusions:

• The developed mirror-mapping based robust control algorithm offers a concise and efficient design for unstable time-delayed processes.
• The method successfully enhances robustness and stability, outperforming conventional approaches.
• The algorithm provides a practical solution for improving control performance in challenging industrial applications.