Parallel cascade control of dead time processes via fractional order controllers based on Smith predictor

Area of Science:

• Control Engineering
• Process Control
• Fractional Calculus

Background:

• Controlling processes with significant time delays, uncertainty, and noise is challenging.
• Existing methods often struggle with stable, unstable, and integrating system dynamics.

Purpose of the Study:

• To develop and evaluate a robust control strategy for complex industrial processes.
• To improve set point tracking and disturbance rejection in systems with large time delays.

Main Methods:

• Design of fractional order controllers within a parallel cascade scheme.
• Integration of a Smith predictor for handling time delays.
• Utilizing Routh-Hurwitz stability criterion for controller design.

Main Results:

• The proposed fractional order controllers show effective control for stable, unstable, and integrating processes.
• Demonstrated robustness against uncertainty, external disturbances, and measurement noise.
• Simulation results confirm the superiority over existing control strategies.

Conclusions:

• The parallel cascade fractional order control strategy with a Smith predictor offers a robust and high-performance solution.
• This approach effectively addresses challenges posed by time delays and system uncertainties.
• The designed controllers provide significant improvements in stability and performance metrics.