Performance-Seeking Control of Aero-Propulsion System Based on Intelligent Optimization and Active Disturbance Rejection Fusion Controller

Abstract

To investigate the performance potential of the aero-propulsion system and the problem of control mode conversion, this paper takes the inlet/engine integrated component-level model as the research object, and a performance-seeking control (PSC) scheme based on the neighborhood-based speciation differential evolution–grey wolf optimization (NSDE-GWO) algorithm is designed and combined with an active disturbance rejection control (ADRC) to establish a multivariable fusion closed-loop control system. The analysis reveals that the NSDE-GWO hybrid algorithm, which takes advantages of the two algorithms, significantly improves the computing efficiency and optimization accuracy, achieving better optimization solutions in three different modes. The intelligent fusion controller is able to achieve a smooth transition of performance modes to ensure that the engine is provided with a stable thrust during operation under supersonic conditions, and the potential for performance optimization is maintained at a reasonable level. Maximum installed thrust mode capable of achieving no thrust loss and a maximum fluctuation rate within 2000 N/s, with the largest variation in thrust during the conversion being less than 0.9% under the minimum turbine temperature mode and the minimum specific fuel consumption mode. This study presents a theoretical foundation and engineering applications for the design of supersonic propulsion system controllers.