基于改进遗传算法的直流锅炉主蒸汽温度自校正控制

Self-tuning control based on improved genetic algorithm for main steam temperature of once-through boiler

针对变负荷下的超(超)临界机组主蒸汽温度控制问题,提出了一种基于改进遗传算法(GA)的自校正控制策略。采用GA辨识被控对象模型参数,并对种群初始化方法和遗传算子部分结构进行了改进;采用最小方差率构造控制器,并结合GA设计了自校正控制的运算流程。对某超临界直流锅炉主蒸汽温度控制的仿真结果表明,所提自校正控制方法具有更快的响应速度和更强的抗干扰能力,能够满足变负荷下的主蒸汽温度控制需求。

A self-tuning control based on GA（Genetic Algorithm） is presented for the main steam temperature of uhra-supercritical unit with variable loads,which identifies the model parameters of controlled object. The method of population initialization and the structure of genetic operators are improved. The generalized minimum variance is employed to construct the controller and the calculating procedure of GA-based self-tuning control is designed. The simulative results of main steam temperature control for an uhra-supercritieal unit show that,the proposed self-tuning control has quicker response and better anti-interference capability, meeting the demands of main steam temperature control for variable loads.