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该文针对石灰石/石膏湿法烟气脱硫工艺中吸收塔浆液pH值变化过程的高度非线性、时滞性以及各种不确定性、常规P ID控制难以达到满意的控制效果,提出了一种基于改进P ID神经网络的内模控制方案,对浆液pH值变化过程进行辨识和控制。仿真结果表明,在改进P ID-NN的内模控制下,吸收塔浆液pH值很好地跟踪了系统的设定输入及其变化,体现了高度的自适应性。同时系统超调量小,稳态精度高,优于常规P ID控制。满足实时控制的要求。
In this paper, aiming at the high nonlinearity, time delay and various uncertainties of the pH value of the absorption tower slurry in the limestone / gypsum wet flue gas desulfurization process, it is difficult to achieve satisfactory control effect by conventional P ID control. Based on the internal model control scheme of improved P ID neural network, the process of pH value change was identified and controlled. The simulation results show that under the control of the internal model with the improved P ID-NN, the pH value of the absorption tower slurry keeps track of the input and its change of the system well, which shows a high degree of self-adaptability. At the same time the system overshoot small, steady high precision, better than the conventional P ID control. Meet real-time control requirements.