针对重油催化裂化分馏塔控制系统满足稳定设计却难以优化系统性能的问题,提出了一种基于多变量ARX-Laguerre函数模型的PID预测控制(multivariable ARX-Laguerre function model predictive control combined with proportion integratio...针对重油催化裂化分馏塔控制系统满足稳定设计却难以优化系统性能的问题,提出了一种基于多变量ARX-Laguerre函数模型的PID预测控制(multivariable ARX-Laguerre function model predictive control combined with proportion integration differentiation,MALMPCPID)算法。以增量式的多变量ARX-Laguerre函数为预测模型,通过带有遗忘因子的最小二乘递归方法在线辨识Laguerre系数矩阵,并将滚动优化的性能指标改写成PID参数形式,以提高系统的动态性能。将所提的MALMPCPID算法应用于Shell公司重油催化裂化分馏塔进行仿真实验并与现有算法进行对比。结果表明,所提算法对多变量强耦合过程具有良好的控制效果,而且快速性和解耦能力得到了大大提高。展开更多
This paper presents the development of a new nonlinear representation by exploiting the multimodel approach and the new linear representation ARX-Laguerre for each operating region. The resulting multimodel, entitled ...This paper presents the development of a new nonlinear representation by exploiting the multimodel approach and the new linear representation ARX-Laguerre for each operating region. The resulting multimodel, entitled ARX-Laguerre multimodel, is characterized by the parameter number reduction with a recursive representation. However, a significant reduction of this multimodel is subject to an optimal choice of Laguerre poles characterizing each local linear model ARX-Laguerre. Therefore, the authors propose an optimization algorithm to estimate, from input/output measurements, the optimal values of Laguerre poles. The ARX-Laguerre multimodel as well as the proposed optimization algorithm are tested on a continuous stirred tank reactor system （CSTR）. Moreover, the authors take into account a practical validation on an experimental communicating two tank system （CTTS）.展开更多
文摘针对重油催化裂化分馏塔控制系统满足稳定设计却难以优化系统性能的问题,提出了一种基于多变量ARX-Laguerre函数模型的PID预测控制(multivariable ARX-Laguerre function model predictive control combined with proportion integration differentiation,MALMPCPID)算法。以增量式的多变量ARX-Laguerre函数为预测模型,通过带有遗忘因子的最小二乘递归方法在线辨识Laguerre系数矩阵,并将滚动优化的性能指标改写成PID参数形式,以提高系统的动态性能。将所提的MALMPCPID算法应用于Shell公司重油催化裂化分馏塔进行仿真实验并与现有算法进行对比。结果表明,所提算法对多变量强耦合过程具有良好的控制效果,而且快速性和解耦能力得到了大大提高。
文摘This paper presents the development of a new nonlinear representation by exploiting the multimodel approach and the new linear representation ARX-Laguerre for each operating region. The resulting multimodel, entitled ARX-Laguerre multimodel, is characterized by the parameter number reduction with a recursive representation. However, a significant reduction of this multimodel is subject to an optimal choice of Laguerre poles characterizing each local linear model ARX-Laguerre. Therefore, the authors propose an optimization algorithm to estimate, from input/output measurements, the optimal values of Laguerre poles. The ARX-Laguerre multimodel as well as the proposed optimization algorithm are tested on a continuous stirred tank reactor system （CSTR）. Moreover, the authors take into account a practical validation on an experimental communicating two tank system （CTTS）.
