推进技术 ›› 2007, Vol. 28 ›› Issue (3): 307-312.

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量子遗传算法在航空发动机PID控制中的应用

孙丰诚,孙健国,张海波   

  1. 南京航空航天大学能源与动力学院 江苏南京210016;南京航空航天大学能源与动力学院 江苏南京210017;南京航空航天大学能源与动力学院 江苏南京210018
  • 发布日期:2021-08-15
  • 基金资助:
    国家自然科学基金项目(50576033);航空科学基金资助项目(04C52019)

Application of quantum genetic algorithm to aero-engine PID control systems

  1. Coll.of Energy and Power,Nanjing Univ.of Aeronautics and Astronautics,Nanjing 210016,China;Coll.of Energy and Power,Nanjing Univ.of Aeronautics and Astronautics,Nanjing 210017,China;Coll.of Energy and Power,Nanjing Univ.of Aeronautics and Astronautics,Nanjing 210018,China
  • Published:2021-08-15

摘要: 分析研究了量子遗传算法(Quantum Genetic A lgorithm-QGA)的原理及其优势,将有指导的群体灾变及多宇宙并行演化策略引入量子遗传算法,改善其收敛性。以理想二阶系统为参考模型,实际系统响应曲线与参考模型响应曲线误差积分为目标函数,使用量子遗传算法进行发动机PID控制器参数优化并进行了数字仿真。仿真结果表明,量子遗传算法具有较好的全局收敛能力,应用于PID控制器控制参数优化后,控制器的控制效果良好,其在发动机控制系统中有较高的应用价值。

关键词: 航空发动机;量子遗传算法+;量子计算+;PID控制器+;参数最优化

Abstract: The theory and advantages of Quantum Genetic Algorithm were analyzed.The guided catastrophe of population and multi-space parallel evolution strategy was added to QGA to improve its global convergence.QGA was applied to aero-engine control systems which use the ideal second-order system to be the reference model.The objective function is the integral of error between aero-engine response and reference model response.QGA was used to optimize aero-engine PID controller parameter.Results of digital simulation were given,which show that QGA has good search capability,and it has application potential in aero-engine control systems.

Key words: Aircraft engine;Quantum genetic algorithm+;Quantum calculation+;PID controller+;Parameter optimization