Design of a robust LMI-based model predictive control method for surge instability in interconnected compressor systems in the presence of uncertainty and disturbance

Abstract

Surge is the most significant instability observed in the compressors, and its control requires the exact dynamics of the compressor systems. Uncertainty in compressor characteristics and unknown opening percentage of the throttle and spillback valves, as well as disturbances in compressor’s flow and pressures, are among the major issues to be addressed in controller design for surge instability. Furthermore, in compressor systems that consist of several individual compressors, their reciprocal effects should also be taken into account. This paper presents an LMI-based decentralized robust model predictive control to ensure the stability of the compressor system against surge instability, uncertainty, and disturbance. The proposed scheme benefits from the optimized control signal with minimum computational complexity to overcome the destabilizing effects in a complex compressor system. The considered working class for this compressor system is a continuous-time nonlinear system. Through this method, the optimization problem is designed for a worst-case scenario. The implementation results of the presented robust controller for a compressor system, consisting of three parallel and series compressors, suggest the effectiveness of the presented method.

Keywords

• model predictive control
• interconnected compressor systems
• lmi-based decentralized control
• surge