Fuzzy Controller Structures Investigation for Future Gas Turbine Aero-Engines

Abstract

The Advisory Council for Aeronautics Research in Europe (ACARE) Flight Path 2050 focuses on ambitious and severe targets for the next generation of air travel systems (e.g., 75% reduction in CO2 emissions per passenger kilometer, a 90% reduction in NOx emissions, and 65% reduction in noise emission of flying aircraft relative to the capabilities of typical new aircraft in 2000). In order to meet these requirements, aircraft engines should work very close to their operating limits. Therefore, the importance of advanced control strategies to satisfy all engine control modes simultaneously while protecting them from malfunctions and physical damages is being more crucial these days. In the last three decades, fuzzy controllers (FCs) have been proposed as a high potential solution for performance improvement of the next generation of aircraft engines. Based on an analytic review, this paper divides the trend of FCs design into two main lines including pure FCs (PFC) and min–max FCs (MMFC). These two main architectures are then designed, implemented on hardware, and applied in a case study to analyze the advantages and disadvantages of each structure. The analysis of hardware-in-the-loop (HIL) simulation results shows that the pure FC structure would be a high potential candidate for maneuverability and response time indices improvement (e.g., military applications); while min–max FC architecture has a great potential for future civil aero-engines where the fuel consumption and steady-state responses are more important. The simulation results are also compared with those of industrial min–max controllers to confirm the feasibility and reliability of the fuzzy controllers for real-world application. The results of this paper propose a general roadmap for fuzzy controllers’ structure selection for new and next generation of aircraft engines.

The Fuzzy Logic in the Problems of Test Control of a Bypass Turbojet Engine Gas Generator

“…It is reasonable to use them for control systems with incomplete or rapidly changing information on the object and with high complexity of the object in the presence of significant multi-variable, nonlinearity, and non-stationarity of its properties and characteristics, which cannot be compensated by the introduction of corrective links and feedback. There are many publications where this approach has been implemented for a variety of objects, for example, in control systems of an aircraft [33], a wind generator [34], a gas turbine engine [35], in a hydrogen vehicle power system [36], in the control system of the tension of an insulating tape in a machine for winding a transformer [37], while controlling the speed of a DC motor [38], in a digital twins of the water cooling system [39], and in a standalone electric vehicle charging station [40].…”