在超临界CO2压缩机运行过程中,可转导叶随压缩机转速等状态变量频繁变化,会引起压缩机喘振,严重时会导致压缩机设备损坏。针对此问题,本文采取了一种基于遗传算法的防喘振自抗扰控制方法,在压气机出口处设置防喘振阀控制喘振,遗传算法整定的自抗扰控制器使防喘振阀的开度随转速等状态变量的变化而作相应地变化,从而改变出口压力来使压缩机工作在平衡点。结果表明,在遗传算法优化后的自抗扰控制器防喘振控制效果更优,调节时间缩短了20%~33%,超调量减少了30%~45%,减缓了到达稳态过程中的震荡,使控制过程更加平滑,能够稳定转速的同时抑制压缩机运行过程中可能出现的扰动。

During the operation of supercritical CO2 compressor, the adjustable guide vane changes frequently with the compressor speed and other state variables, which will cause the compressor to surge, and in serious cases the compressor equipment will be damaged. To solve this problem, this paper adopts an anti-surge auto-disturbance-rejection control method based on genetic algorithm. An anti-surge valve is set at the outlet of the compressor to control the surge. The auto-disturbance-rejection controller set by genetic algorithm makes the opening of the anti-surge valve change with the change of state variables such as speed, so as to change the outlet pressure to make the compressor work at the balance point. The results show that the anti-surge control effect of the auto disturbance rejection controller optimized by genetic algorithm is better, the adjustment time is shortened by 20%~33%, the overshoot is reduced by 30%~45%, the oscillation in the process of reaching the steady state is slowed down, the control process is smoother, and the possible disturbance in the compressor operation process can be suppressed while maintaining stable speed.

TK221

国家自然科学基金项目（面上项目，重点项目，重大项目）；江苏省基础研究计划（自然科学基金）青年基金项目