Strong stabilization servo controller with optimization of performance criteria

Area of Science:

• Control Systems Engineering
• Robotics
• Electrical Engineering

Background:

• Servo mechanisms require precise control for optimal performance.
• Brushless DC (BLDC) and Brush DC (BDC) motors are widely used in various applications.
• Ensuring robustness and stability in control systems is critical, especially under varying conditions.

Purpose of the Study:

• To synthesize a simple, robust controller for servo mechanisms.
• To utilize pole placement techniques and H(∞) metrics for controller design.
• To ensure the stability and robustness of closed-loop systems with BLDC and BDC motors.

Main Methods:

• Pole placement technique combined with H(∞) metrics for controller synthesis.
• Solving polynomial equations using Manabe standard polynomial form and parametric solutions.
• Robustness assessment using uncertainty models and the H(∞) norm.
• Optimization using a genetic algorithm, specifically Differential Evolution (DE).
• Stability verification using Šiljak's absolute stability test and Lipatov's stability condition.

Main Results:

• A robust servo controller structure was successfully designed and optimized.
• The controller demonstrated robustness against system uncertainties.
• The DE optimization effectively determined suboptimal solutions for the controller.
• Šiljak's test and Lipatov's condition confirmed the stability and robustness characteristics.

Conclusions:

• The proposed method provides a simple and robust controller for servo mechanisms.
• The integration of pole placement, H(∞) metrics, and DE optimization is effective.
• The polynomial-based stability tests are suitable for automated control design and optimization.