Optimization and Its Implementation Impact of Two-Modes Controller Fractional Approximation for Buck Converters

Area of Science:

• Electrical Engineering
• Control Systems Engineering

Background:

• Fractional-order control offers enhanced performance for power electronic converters.
• Current tuning methods lack reliability, often yielding non-viable controller parameters.
• Artificial intelligence techniques for tuning may not guarantee realizable structures or reachable parameter values.

Purpose of the Study:

• To develop and validate a fractional-order control strategy with adjustment boundaries for power electronic converters.
• To ensure controller viability and robustness while maintaining performance.
• To compare particle swarm and genetic optimization algorithms for controller tuning.

Main Methods:

• Described the fractional-order approach using the El-Khazali biquadratic module for lowest order approximation.
• Synthesized a two-modes controller structure based on plant requirements.
• Employed particle swarm and genetic optimization algorithms with error-based minimization criteria.
• Incorporated constraints for robustness and to prevent high-gain controllers.

Main Results:

• Optimization results showed similar minima with and without constraints.
• Significant differences in controller parameters were observed between constrained and unconstrained optimization.
• Numerical and experimental results validated the effectiveness of the proposed constrained approach.

Conclusions:

• The proposed constraints ensure the synthesis of viable and robust fractional-order controllers for power electronic converters.
• The method effectively balances performance, robustness, and practical design considerations.
• Validated effectiveness through numerical simulations and experimental implementation.