A novel predictive control algorithm and robust stability criteria for integrating processes.

Area of Science:

• Control Engineering
• Process Control

Background:

• Integrating systems present challenges in control due to their inherent characteristics.
• Existing control methods often require pre-stabilization, adding complexity.
• Unmeasured disturbances can lead to permanent offsets in control systems.

Purpose of the Study:

• To introduce a novel predictive controller for single-input/single-output (SISO) integrating systems.
• To enable direct application of the controller without process pre-stabilization.
• To enhance robustness and eliminate steady-state errors in the presence of disturbances.

Main Methods:

• Development of a control algorithm based on a tested step response model.
• Proposal of a predictive feedback error compensation method to eliminate offset.
• Introduction of a rotator factor in the performance index for improved robustness.
• Derivation of a robust stability condition using Jury's dominant coefficient criterion.

Main Results:

• The proposed controller effectively manages the integrating mode and compensates for unmeasured disturbances.
• A novel feedback error compensation method eliminates permanent offset.
• The rotator factor enhances the robustness of the closed-loop system.
• The controller has only two easily tunable parameters with clear physical meanings.

Conclusions:

• The novel predictive controller offers direct applicability and eliminates the need for pre-stabilization.
• The controller demonstrates excellent closed-loop performance, outperforming reported methods in simulations.
• The method provides a robust and easily implementable solution for controlling SISO integrating systems.