基于模糊ARX模型的水泥回转窑预测控制算法研究
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摘要
水泥回转窑是新型干法水泥生产线的核心设备，水泥生产过程中最关键的生料煅烧理化反应在回转窑内进行，回转窑的控制水平直接影响水泥的质量、产量以及能耗。研究水泥回转窑的建模及控制方法，对提高水泥回转窑的控制水平具有重要的理论和实际意义。本课题针对新型干法水泥回转窑煅烧过程具有的多时滞、多变量、非线性的特性，在对采样数据分析处理的基础上，运用组合模型建模理论、预测控制理论，基于模糊ARX模型对水泥回转窑的预测控制算法进行了研究，具体研究工作如下：
首先，依据水泥回转窑的煅烧机理，分析影响水泥熟料质量及能耗的控制因素，研究参量间的变化规律。利用相关函数法分析控制参量的测试数据，确定回转窑煅烧系统建模变量，以回转窑窑尾烟室的氮氧化物含量，氧气含量和窑尾温度为控制目标量，以窑头喂煤量，高温风机挡板开度和料速积为操作变量，为建立水泥回转窑煅烧过程的预测模型提供基础。
其次，基于系统稳态非线性特性和动态线性特性分离辨识的组合模型建模思想，提出基于T-S模糊模型的ARX模型增益实时修正方法，建立适用于多变量非线性系统的变增益模糊ARX模型；以数据驱动思想为基础，提出一种数据驱动模糊辨识改进算法，建立系统测试数据不能覆盖所有输入变量约束范围情况下的水泥回转窑煅烧系统稳态模型；运用外推差值法计算系统的实际动态增益来实时修正多时滞ARX模型的增益，提高建模的准确性，进而提出多时滞多变量非线性系统的变增益模糊ARX模型建模方法，以解决回转窑多时滞特性的建模问题；在对水泥回转窑的稳态和动态辨识数据分开进行预处理的基础上，建立水泥回转窑煅烧过程控制系统预测模型。
进一步，采用序列二次规划优化算法，实时动态求解多变量非线性系统的输入变化量，构建基于多变量模糊ARX模型的预测控制算法。在此基础上，提出系数矩阵插值组合法，将多时滞加入到多变量非线性系统的多步预测输出表达式，建立基于多时滞变增益模糊ARX模型的预测控制算法，以实现回转窑煅烧过程的多时滞控制，进而建立水泥回转窑煅烧系统的预测控制算法。
最后，利用现场DCS系统采集的水泥回转窑测试数据，进行数据的建模与分析，采用本文建立的水泥回转窑多时滞变增益模糊ARX模型及其预测控制算法，对水泥回转窑煅烧过程进行预测控制实验研究，验证本文提出算法的可行性和有效性。
Cement rotary kiln is the core equipment of the NSP cement production line, themost critical calcinations’ physical and chemical reactions of the raw material in thecement production is conducting in the kiln; the control level of the kiln has a directimpact on the production, quality and energy consumption. The research on modeling andcontrol method for the cement rotary kiln has important theoretical and practicalsignificance to improve the control level of the cement rotary kiln. For that thecalcinations’ process of the NSP cement rotary kiln has the characteristics of nonlinear,multivariable and multi-delay, on the basis of analysis process to the sample data, thispaper uses the combined modeling theory and the predictive control theory to study thepredictive control method of the cement rotary kiln based on fuzzy ARX model, specificresearch work are shown as follows:
First of all, according to the calcined mechanism of the cement rotary kiln, thecontrol factors that affect the quality and energy consumption of the cement clinker isanalyzed, the variation between the parameters are studied. The correlation functionmethod is used to analyze the test data of control parameters, and then the modelingvariables of the rotary kiln system are determined. The nitrogen oxides content in thesmoke room that is at the end of rotary kiln, oxygen content and temperature at the end ofthe rotary kiln are set as the control targets, and the amount of feeding coal at the head ofthe kiln, the baffle opening of high temperature fan and feeding speed area are set as theoperating variables. All these works provide the basis for the establishment of theprediction model for the cement rotary kiln calcinations’ process.
Secondly, according to the combined modeling idea based on the separationidentification of nonlinear characteristic and dynamic linear characteristic in systemsteady state, the real gain correction method of ARX model based on T-S fuzzy model isproposed and the variant gain fuzzy ARX suiting for the multi-variable nonlinear systemis worked out. On basis of data driver thought, this paper puts forward a data driven fuzzyidentification improved algorithm and establishes cement rotary kiln calcining system steady model under the condition that the system test data can not cover all input variableconstraint range. Use the push difference method to calculate the actual system dynamicgain for real-time correction of multi-delay ARX model gain and improve the accuracy ofthe model, and then put forward the variable gain fuzzy ARX model method formulti-delay multivariable nonlinear system in order to solve the modeling problem ofmuch delay characteristics in the rotary kiln. Based on the separately preprocessing ofsteady state and dynamic identification data in the cement rotary kiln, the control systemprediction model of cement rotary kiln calcining process is established.
Furthermore, the sequential quadratic programming optimization algorithm isutilized to dynamically solve the input change of multivariable nonlinear system and apredictive control algorithm based on multivariable fuzzy ARX model is developed. Onthis basis, the coefficient matrix interpolation combination method is proposed, and themulti-delay is added into the multi-step prediction output expression of the multivariablenonlinear system. And then a predictive control algorithm of the multi-delay multivariablefuzzy ARX model is designed so as to realize the multi-time delay control of rotary kilnsintering process, and then the prediction control algorithm for the cement rotary kilncalcine system was designed.
Finally, using the DCS system to collect the test data of cement rotary kiln, and thedata is modeled and analyzed. According to the proposed multi-time delay variable gainfuzzy ARX model and its prediction algorithm of cement rotary kiln in this paper, thepredictive control experiment of cement rotary kiln is performed. The experimentalresults can reveal that the feasibility and validity of the proposed algorithms in this paper.
首先，依据水泥回转窑的煅烧机理，分析影响水泥熟料质量及能耗的控制因素，研究参量间的变化规律。利用相关函数法分析控制参量的测试数据，确定回转窑煅烧系统建模变量，以回转窑窑尾烟室的氮氧化物含量，氧气含量和窑尾温度为控制目标量，以窑头喂煤量，高温风机挡板开度和料速积为操作变量，为建立水泥回转窑煅烧过程的预测模型提供基础。
其次，基于系统稳态非线性特性和动态线性特性分离辨识的组合模型建模思想，提出基于T-S模糊模型的ARX模型增益实时修正方法，建立适用于多变量非线性系统的变增益模糊ARX模型；以数据驱动思想为基础，提出一种数据驱动模糊辨识改进算法，建立系统测试数据不能覆盖所有输入变量约束范围情况下的水泥回转窑煅烧系统稳态模型；运用外推差值法计算系统的实际动态增益来实时修正多时滞ARX模型的增益，提高建模的准确性，进而提出多时滞多变量非线性系统的变增益模糊ARX模型建模方法，以解决回转窑多时滞特性的建模问题；在对水泥回转窑的稳态和动态辨识数据分开进行预处理的基础上，建立水泥回转窑煅烧过程控制系统预测模型。
进一步，采用序列二次规划优化算法，实时动态求解多变量非线性系统的输入变化量，构建基于多变量模糊ARX模型的预测控制算法。在此基础上，提出系数矩阵插值组合法，将多时滞加入到多变量非线性系统的多步预测输出表达式，建立基于多时滞变增益模糊ARX模型的预测控制算法，以实现回转窑煅烧过程的多时滞控制，进而建立水泥回转窑煅烧系统的预测控制算法。
最后，利用现场DCS系统采集的水泥回转窑测试数据，进行数据的建模与分析，采用本文建立的水泥回转窑多时滞变增益模糊ARX模型及其预测控制算法，对水泥回转窑煅烧过程进行预测控制实验研究，验证本文提出算法的可行性和有效性。
Cement rotary kiln is the core equipment of the NSP cement production line, themost critical calcinations’ physical and chemical reactions of the raw material in thecement production is conducting in the kiln; the control level of the kiln has a directimpact on the production, quality and energy consumption. The research on modeling andcontrol method for the cement rotary kiln has important theoretical and practicalsignificance to improve the control level of the cement rotary kiln. For that thecalcinations’ process of the NSP cement rotary kiln has the characteristics of nonlinear,multivariable and multi-delay, on the basis of analysis process to the sample data, thispaper uses the combined modeling theory and the predictive control theory to study thepredictive control method of the cement rotary kiln based on fuzzy ARX model, specificresearch work are shown as follows:
First of all, according to the calcined mechanism of the cement rotary kiln, thecontrol factors that affect the quality and energy consumption of the cement clinker isanalyzed, the variation between the parameters are studied. The correlation functionmethod is used to analyze the test data of control parameters, and then the modelingvariables of the rotary kiln system are determined. The nitrogen oxides content in thesmoke room that is at the end of rotary kiln, oxygen content and temperature at the end ofthe rotary kiln are set as the control targets, and the amount of feeding coal at the head ofthe kiln, the baffle opening of high temperature fan and feeding speed area are set as theoperating variables. All these works provide the basis for the establishment of theprediction model for the cement rotary kiln calcinations’ process.
Secondly, according to the combined modeling idea based on the separationidentification of nonlinear characteristic and dynamic linear characteristic in systemsteady state, the real gain correction method of ARX model based on T-S fuzzy model isproposed and the variant gain fuzzy ARX suiting for the multi-variable nonlinear systemis worked out. On basis of data driver thought, this paper puts forward a data driven fuzzyidentification improved algorithm and establishes cement rotary kiln calcining system steady model under the condition that the system test data can not cover all input variableconstraint range. Use the push difference method to calculate the actual system dynamicgain for real-time correction of multi-delay ARX model gain and improve the accuracy ofthe model, and then put forward the variable gain fuzzy ARX model method formulti-delay multivariable nonlinear system in order to solve the modeling problem ofmuch delay characteristics in the rotary kiln. Based on the separately preprocessing ofsteady state and dynamic identification data in the cement rotary kiln, the control systemprediction model of cement rotary kiln calcining process is established.
Furthermore, the sequential quadratic programming optimization algorithm isutilized to dynamically solve the input change of multivariable nonlinear system and apredictive control algorithm based on multivariable fuzzy ARX model is developed. Onthis basis, the coefficient matrix interpolation combination method is proposed, and themulti-delay is added into the multi-step prediction output expression of the multivariablenonlinear system. And then a predictive control algorithm of the multi-delay multivariablefuzzy ARX model is designed so as to realize the multi-time delay control of rotary kilnsintering process, and then the prediction control algorithm for the cement rotary kilncalcine system was designed.
Finally, using the DCS system to collect the test data of cement rotary kiln, and thedata is modeled and analyzed. According to the proposed multi-time delay variable gainfuzzy ARX model and its prediction algorithm of cement rotary kiln in this paper, thepredictive control experiment of cement rotary kiln is performed. The experimentalresults can reveal that the feasibility and validity of the proposed algorithms in this paper.
引文
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