Demonstrates improved control performance with adaptive fuzzy PID controller in gas flow regulation, indicating enhanced energy efficiency.
Flow adjustable gas generators enable precise energy distribution tailored to the diverse operating demands of aircraft, thus reducing energy loss. While these devices have been widely adopted in modern propulsion systems due to their energy efficiency driven advantages, persisting limitations hinder their full potential under complex conditions. To deal with the significantly nonlinear and time-varying characteristics of the gas flow regulation system for flow adjustable gas generators, an adaptive fuzzy proportional-integral-derivative (PID) controller based on genetic algorithm optimization is developed, in which the quantification and proportionality factors are adaptively tuned using the genetic algorithm. The objective function of the genetic algorithm is improved by comprehensively considering the effects of overshoot and response time. The control performance of this controller is then compared with that of fuzzy PID controllers and classical PID controllers under various operating conditions. The findings convincingly demonstrate that during prolonged operation of the gas flow regulation system, the adaptive fuzzy PID controller, compared with the two counterparts, reduces the overshoot by 92.9% and 95.8% and shortens the response time by 31.8% and 35.7%, respectively. Meanwhile, it also exhibits superior advantages in maintaining system stability in the presence of control signal disturbances or system parameter variations. Therefore, this adaptive fuzzy PID controller based on genetic algorithm optimization displays the best comprehensive control performance, which can ensure continuous, efficient, and stable operation of the gas flow regulation system, thus further improving the energy utilization efficiency of the solid rocket ramjet.
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Wang et al. (2026) studied this question.
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