Deep optimization design of 2D repetitive control systems with saturating actuators: An adaptive multi-population PSO...

Area of Science:

• Control Systems Engineering
• Robotics and Automation
• Optimization Theory

Background:

• Repetitive control systems (RCS) are effective for tracking periodic signals but can be sensitive to actuator saturation.
• Existing methods for designing modified repetitive control systems (MRCS) often struggle with optimizing performance under saturation constraints.
• Actuator saturation can lead to performance degradation and instability in control systems.

Purpose of the Study:

• To develop an optimization design method for a two-dimensional modified repetitive control system (MRCS) with an anti-windup compensator.
• To ensure the stability and enhance the reference-tracking performance of the MRCS, especially in the presence of actuator saturation.
• To reduce the optimization time by introducing a novel cost function for direct performance evaluation.

Main Methods:

• A two-dimensional hybrid model of the MRCS, incorporating actuator saturation, was established using lifting technology.
• A linear-matrix-inequality (LMI)-based sufficient condition was derived to guarantee system stability.
• An adaptive multi-population particle swarm optimization algorithm was employed with a new time-domain cost function to optimize critical tuning parameters.

Main Results:

• The proposed LMI-based condition ensures the stability of the MRCS.
• The novel cost function effectively evaluates control performance, reducing optimization time.
• The adaptive multi-population particle swarm optimization successfully identified optimal tuning parameters.
• The addition of an anti-windup term mitigated the adverse effects of actuator saturation.

Conclusions:

• The developed optimization design method effectively improves the performance and stability of 2D MRCS with anti-windup compensation.
• The approach is validated through simulations and experimental results on a rotation control system.
• The method offers a robust solution for control systems facing actuator saturation challenges.