摘要
If accuracy and calculation ability are taken into account at the same time, the existing control strategies for aero-engine are too conservative to obtain reasonable dynamic behavior. Based on ANN model-free adaptive control theory and biological endocrine intelligent principle, an integrated MFAIC control algorithm for aero-engine consists with off-line and on-line online part is put forward. First of all, in the off-line module, ANN network is implemented to calculate control parameters over full flight envelope of the turbo-fan engine, setting reference for the on-line module. On this basis, control parameters are updated automatically according to the real-time I/O data and errors until errors are eliminated. Then, the biological endocrine intelligent control(BEIC) is added for online further optimization. In a word, the main structure and all the functions of the non-model adaptive bio-intelligent controller are improved. After that, the control effect and the anti-disturbance ability of the MACIC and other conventional control methods in dynamic process are verified in detail. It can be seen from simulation results that the integrated MFAIC method shows advantages in stability robustness. In conclusion, the method of MFAIC possess practical significance in engineering.
If accuracy and calculation ability are taken into account at the same time, the existing control strategies for aero-engine are too conservative to obtain reasonable dynamic behavior. Based on ANN model-free adaptive control theory and biological endocrine intelligent principle, an integrated MFAIC control algorithm for aero-engine consists with off-line and on-line online part is put forward. First of all, in the off-line module, ANN network is implemented to calculate control parameters over full flight envelope of the turbo-fan engine, setting reference for the on-line module. On this basis, control parameters are updated automatically according to the real-time I/O data and errors until errors are eliminated. Then, the biological endocrine intelligent control(BEIC) is added for online further optimization. In a word, the main structure and all the functions of the non-model adaptive bio-intelligent controller are improved. After that, the control effect and the anti-disturbance ability of the MACIC and other conventional control methods in dynamic process are verified in detail. It can be seen from simulation results that the integrated MFAIC method shows advantages in stability robustness. In conclusion, the method of MFAIC possess practical significance in engineering.
引文
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