300MW机组锅炉主蒸汽温度智能控制优化策略

Optimization Strategy of Intelligent Control for Main Steam Temperature of 300MW Unit Boiler

为有效地解决主蒸汽温度控制系统的大延时控制难点,在Smith预估优化的基础上提出了一种基于惯性滤波的Smith预估串级控制策略,目的是降低传统Smith预估控制对模型的敏感度。以模糊理论为基础设计模糊PID控制器,期望通过专家经验解决难以建立数学模型的问题。然后,通过快速粒子群(PSO)算法对模糊模块的量化因子和比例因子进行寻优,得到最优值,该控制系统计算量小且控制效果较好,具有一定的实际应用价值。

For the effective control of the difficult point about main steam temperature control system with large delay, on the basis of Smith’s prediction optimization, a Smith predictive cascade control strategy based on inertial filtering is proposed to reduce the sensitivity of the traditional Smith predictive control to the model. To solve the problem a fuzzy-PID controller is designed based on the fuzzy theory as it is difficult to establish mathematical model through expert experience. Then, the quantization factor and scale factor of the fuzzy module are optimized by the fast Particle Swarm Optimization(PSO) algorithm, and the optimal value is obtained. This control system has less calculation and better control effect, which has certain practical application value.