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PID控制器的参数整定在蒸发器液位的控制中占有十分重要的地位,为了使蒸发器的液位控制更加准确,采用遗传算法对PID参数进行整定。标准遗传算法对PID优化的结果表明该算法容易出现早熟现象,而且不稳定。进而提出了改进的双种群遗传算法,将改进后的算法对PID参数进行优化,结果表明双种群遗传算法的搜索结果明显好于标准遗传算法,而且克服了标准遗传算法在参数优化问题上表现出缺点。因此,将其应用于蒸发器的液位控制中,可以使蒸发器的设计更加准确,具有一定的推广应用价值。
PID controller parameter setting in the evaporator level control plays a very important position, in order to make the evaporator level control more accurate, using genetic algorithm to set the PID parameters. The results of standard genetic algorithm for PID optimization show that the algorithm is prone to premature, but unstable. Furthermore, an improved two-population genetic algorithm is proposed, and the improved algorithm is used to optimize the PID parameters. The results show that the search results of the two-population genetic algorithm are obviously better than the standard genetic algorithm, and overcome the problem that the standard genetic algorithm Disadvantages. Therefore, when applied to the liquid level control of the evaporator, the design of the evaporator can be more accurate and has certain promotion and application value.