GOA-Optimized Control Strategy for Stall and Surge in Centrifugal Compressors

Abstract

As core power equipment, the stable operation of centrifugal compressors is critical to industrial systems. Stall and surge represent severe unstable operating conditions that threaten compressor safety, potentially leading to equipment damage and production interruptions. To address the limitations of traditional control strategies in handling system nonlinearity, time-varying characteristics, and model uncertainty, this paper proposes an intelligent control method based on the Grasshopper Optimization Algorithm (GOA). The study first establishes a nonlinear model that accurately reflects the compressor's dynamic characteristics. Subsequently, advanced controllers (such as fuzzy PID and model predictive controllers) are designed with the objectives of expanding stability margin and suppressing pressure pulsations. To tackle the challenge of tuning critical controller parameters, the GOA algorithm is employed for global optimization. Leveraging its robust optimization capabilities and convergence speed, it adaptively obtains optimal parameter combinations to enhance the system's dynamic response performance and disturbance rejection capability. Simulation and experimental results demonstrate that compared to conventional PID and empirical tuning methods, the GOA-optimized control strategy more effectively delays the surge onset boundary, rapidly suppresses pressure oscillations under disturbance conditions, and significantly enhances the operational stability and control quality of centrifugal compressors. This provides a novel solution for the safe, efficient, and intelligent operation of compressors.