Advanced constraints management strategy for real-time optimization of gas turbine engine transient performance - Nikolaidis, Theoklis; Jafari, Soheil; Li, Zhuo (MDPI, 2019)
Motivated by the growing technology of control and data processing as well as the increasingly complex designs of the new generation of gas turbine engines, a fully automatic control strategy that is capable of dealing with different aspects of operational and safety considerations is required to be implemented on gas turbine engines. An advanced practical control mode satisfaction method for the entire operating envelope of gas turbine engines is proposed in this paper to achieve the optimal transient performance for the engine. A constraint management strategy is developed to generate different controller settings for short-range fighters as well as long-range intercontinental aircraft engines at different operating conditions by utilizing a model predictive control approach. Then, the designed controller is tuned and modified with respect to different realistic considerations including the practicality, physical limitations, system dynamics, and computational efforts. The simulation results from a verified two-spool turbofan engine model and controller show that the proposed method is capable of maneuverability and/or fuel economy optimization indices while satisfying all the predefined constraints successfully. Based on the parameters, natural frequencies, and dynamic behavior of the system, a set of optimized weighting factors for different engine parameters is also proposed to achieve the optimal and safe operation for the engine at different flight conditions. The paper demonstrates the effects of the prediction length and control horizon; adding new constraints on the computational effort and the controller performance are also discussed in detail to confirm the effectiveness and practicality of the proposed approach in developing a fully automatic optimized real-time controller for gas turbine engines.
Keywords: gas turbine engine; transient performance optimization; model predictive control; constraints management; control modes satisfaction; real-time optimization