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针对超超临界机组的主汽温控制,提出了一种广义预测PID控制方法,该方法采用改进遗传算法对PID控制器参数进行在线优化.采用了一种基于广义预测控制性能指标的遗传算法寻优思路,建立了主、副回路PID参数优化模型;在选择、交叉和变异算子方面,初始种群设计方面和交叉、变异概率调整方面对遗传算法进行了改进.最后对广东潮州电厂某锅炉现场连续运行的历史数据进行了控制仿真,结果表明采用基于改进遗传算法的预测PID控制策略后,系统在动、静态特性和变负荷能力上均比常规串级系统效果更好.
Aiming at the main steam temperature control of ultra supercritical units, a generalized predictive PID control method is proposed, which uses an improved genetic algorithm to optimize the PID controller parameters online. A genetic algorithm based on generalized predictive control Yushu Road, the optimization model of PID parameters of primary and secondary circuits was established, and the genetic algorithm was improved in terms of selection, crossover and mutation operator, initial population design and crossover and mutation probability adjustment.Finally, The simulation results show that the system has better performance than the conventional cascade system in the dynamic and static characteristics and variable load capacity by using the predictive PID control strategy based on the improved genetic algorithm.