Pressure Control of Centrifugal Fan Using Softsign-PI Controller Tuned by Hybrid Starfish Optimization Algorithm with...

Area of Science:

• Engineering
• Control Systems
• Fluid Dynamics

Background:

• Induction-motor-driven centrifugal fans require precise pressure regulation for efficiency.
• Existing control methods often struggle with nonlinear dynamics and parameter tuning.

Purpose of the Study:

• To introduce a Softsign-PI controller combined with a hybrid optimization algorithm (hSFOA-DE) for improved fan pressure control.
• To evaluate the proposed controller's performance against various modern and classical control tuning methods.

Main Methods:

• Development of a Softsign-PI controller incorporating a Softsign nonlinearity for error shaping.
• Implementation of a hybrid starfish optimization with differential evolution (hSFOA-DE) for automatic controller parameter tuning.
• Validation on an experimentally validated nonlinear fan-motor model and benchmarking against metaheuristics and classical PID tunings.

Main Results:

• The hSFOA-DE tuned Softsign-PI controller demonstrated superior performance in statistical summaries and time-domain metrics.
• Achieved faster convergence, reduced run-to-run variability, and improved transient and steady-state behavior.
• Exhibited the lowest Zwe-Lee Gaing (ZLG) and integral of absolute error (IAE) values, indicating enhanced robustness and tracking accuracy.

Conclusions:

• The proposed Softsign-PI controller with hSFOA-DE offers significant advantages in pressure regulation for centrifugal fans.
• The approach leads to reduced overshoot and cumulative error, potentially lowering throttling losses and actuator duty.
• Potential benefits include energy savings and reduced maintenance in fan and pump applications.