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电厂过热汽温对象具有大惯性、大迟延和非线性等特性,常规控制策略难取得满意的控制效果。为此,提出一种基于免疫优化的智能预测控制方法,它将离线辨识得到的模型作为预测模型,然后利用实数编码的免疫优化算法在线实现预测控制的滚动优化,给出每个采样时刻的最优控制量。将其应用于过热汽温控制系统进行仿真研究,结果表明该智能预测控制方法具有优良的控制品质。
The superheated steam temperature in the power plant has the characteristics of large inertia, large delay and nonlinearity, and it is difficult to obtain the satisfactory control effect in the conventional control strategy. Therefore, a new intelligent predictive control method based on immune optimization is proposed, which takes the offline recognition model as the predictive model, and realizes the rolling optimization of predictive control online by using the real-coded immune optimization algorithm. Excellent control volume. The simulation results show that the intelligent predictive control method has excellent control quality.