Abstract

More electric engine (MEE) with electric pump metering fuel has the problem of unstable engine control due to the dead-zone characteristics of afterburner fuel actuator. On the basis of conventional μ modified adaptive control method, a compound modified adaptive control (CMAC) system based on neural network inverse model is proposed in this study. At first, the afterburner fuel actuator model of MEE is established through Simulink/AMESim co-simulation to study its fuel supply characteristics and reveal the reasons for dead-zone characteristics of the actuator. Subsequently, an integrated model of afterburner fuel actuator/MEE is established to investigate the effect of dead-zone characteristics on engine performance. Finally, the CMAC system for afterburner fuel flow closed-loop control based on neural network inverse model and improved μ modified adaptive control method is designed. The simulation results show that the dead-zone characteristics of afterburner fuel actuator can cause engine shaking and unstable operation. The engine thrust has a continuous fluctuation with amplitude of about 0.2%. The proposed CMAC system can effectively avoid the dead-zone interval of actuator and achieve stable transition of the engine state in the entire operating range of the afterburner fuel actuator. Thus, the stability of the control system can be significantly improved. Meanwhile, the improved μ modified adaptive control algorithm in the CMAC system has better dynamic characteristics when compared with the conventional μ modified adaptive control algorithm.

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