【作者】 王妍；

【导师】 高宪文；

【作者基本信息】 东北大学 ， 控制理论与控制工程， 2012， 硕士

【摘要】 焦炭是冶金工业炼铁的主要原料,在炼焦生产过程中同时伴随产生大量的副产品—荒煤气。集气过程中有效回收利用荒煤气,不仅节约能源,而且减少环境污染,是钢铁生产的重要环节。焦炉集气管压力是炼焦生产中的重要参数,它的稳定性直接影响着焦炭质量、焦炉的使用寿命以及企业的效益。由于集气管压力系统是一个多变量、非线性、强耦合的复杂系统,传统的控制方法难以达到理想的控制效果,目前钢铁厂还是大多数采用PID和现场操作人员手动调节相结合的方法,智能程度较低,存在产品质量不稳定,能源消耗高等问题,因此研究焦炉集气管压力系统的建模和控制方法具有重要的意义。本文首先分析焦炉集气工艺过程,在研究影响焦炉压力稳定因素的基础上,运用T-S模糊建模方法对集气过程进行建模,建立焦炉集气管压力系统的非线性模型,利用模糊C-均值聚类算法和最小二乘法分别辨识前后件的结构和参数。进一步将该模型转化为线性时变状态空间模型运用于后续的控制算法中。然后针对线性时变系统提出了一种基于椭圆不变集的双模预测控制方法。首先不考虑系统受限,设计最优控制律和终端不变集；然后针对系统受限引入辅助控制变量,控制律的求解可以转化为二阶锥规划问题,从而实现对集气管压力的控制。这种方法通过在最优控制的基础上增加补偿量,以此扩大可行不变集的范围,既保证了系统的可行性,也提高了系统的稳定性能。最后,本文设计了焦炉集气管压力的控制系统,仿真研究表明,双模预测方法具有快速调节性,能够将集气管压力稳定在工艺范围内,控制效果良好。更多还原

【Abstract】 Coke is the main raw material in the metallurgical industry. In the coking process, large amount of by-product gas will be generated from coke ovens, recycling by-product gas in the gas collecting process is an important link in the iron and steel production, which not only saves energy but reduces environmental pollution. The stability of gas collector pressure is an important parameter in the coking process, which directly affects the quality of coke, the life-time of coke ovens and enterprise benefit. The gas collecting process of coke ovens is a complex multi-variable, nonlinear and strong coupling industrial process, so it is hard to acquire good control results with traditional modeling methods and classical control theory. Currently, most steel plants use the PID control combined with the work experience of the site operators. But it suffers many troubles, such as low automation, unstable product quality and high energy consumption. Therefore, the research on the modeling and control method of collector pressure in coke oven has great significance.This paper first analyses the process of coke oven gas collection and the different factors which affected the collector pressure control. Based on it, establishing the nonlinear model of coke oven collector pressure process applies the T-S fuzzy modeling method. Antecedent and consequent of T-S model are identified apart. Fuzzy c-means clustering algorithm is used to identify antecedent parameter and structure. Consequent parameter is identified by least square method. Furthermore, T-S model is transformed to a linear time-varying state space model for the following control algorithm.Second, due to the linear time-varying state space model, this paper proposes a dual-mode model predictive control algorithm based on ellipsoidal invariant set. First the optimal controller is designed without regarding to the input constraints. Then the free future control moves is enhanced when considering the constraints. The control law can be obtained by solving an SOCP optimization problem. The scope of the invariant sets is enlarged by enhancing the additional term based on the optimal control which can guarantee the feasibility and stability of the algorithm.Finally, a control system of gas-collector pressure for coke oven is designed, the results of simulation show the gas-collector pressure can be controlled in a certain region and the effect of the control is good.更多还原