动态软测量建模方法初探

经过十几年的发展,软测量技术无论是在理论研究还是在实际应用中均取得了较大成功,然而至今为止的大部分研究都是针对静态软测量模型.分析了静态软测量模型与动态软测量模型之间的区别和联系,利用冲激响应模型给出了一个基于最小二乘方法的动态软测量建模方法,并在该方法的基础上给出了一种改进.仿真例子验证了该方法及其改进的有效性.     

基于小波网络模型的EPI过程的控制和优化

针对具有强非线性、大纯滞后特性的EPI反应分馏生产过程的废液DOC体积分数控制这一控制难题,应用小波神经网络模型和结合机理分析模型及小波神经网络模型的混合模型结构进行实际EPI反应分馏生产过程的建模控制和优化,提出了基于稳态小波神经网络模型的优化和基于动态小波神经网络模型的非线性预测控制两层结构的整体解决方案,在实际生产过程中获得了成功的应用,不仅使生产过程平稳运行,而且显著地降低排放废液中的DOC体积分数,达到了环保的标准。所提出的技术适合于许多连续反应系统。     

基于混杂策略的预测控制不可行与约束优先级处理

A hybrid approach using MLD (mixed logical dynamical) framework to handle infeasibility and constraint prioritization issues in MPC (model predictive control) based on input-output model is introduced. By expressing constraint priorities as propositional logics and by transforming the propositional logics into inequalities,the infeasibility and constraint prioritization issues are solved in the MPC. Constraints with higher priorities are met first, and then these with lower priorities are satisfied as much as possible. This new approach is illustrated in the control of a heavy oil fractionator-Shell column. The overall control performance has been significantly improved through the infeasibility and control priorities handling.     

一类非线性时滞过程的主动容错控制

Based on a nonlinear state predictor (NSP) and a strong tracking filter (STF), a sensor fault tolerant generic model control (FTGMC) approach for a class of nonlinear time-delay processes is proposed. First, the NSP is introduced, and it is used to extend the conventional generic model control (GMC) to nonlinear processes with large input time-delay. Then the STF is adopted to estimate process states and sensor biaz, the estimated sensor bias is used to drive a fault detection logic. When a sensor fault is detected, the estimated process states by the STF will be used to construct the process output to form a “soft sensor“, which is then used by the NSP (instead of the real outputs) to provide state predictors. These procedures constitute an active fault tolerant control scheme. Finally, simulation results of a three-tank-system demonstrate the effectiveness of the proposed approach.     

稳态目标优化的稳定MIMO约束预测控制

A two-stage multi-objective optimization model-predictive control algorithms(MPC) strategy is presented. A domain MPC controller with input constraints is used to increase freedom for steady-state objective and enhance stabilization of the controller. A steady-state objective optimization algorithm oriented to transient process is adopted to realize optimization of objectives else than dynamic control. It is proved that .the stabilization for both dynamic control and steady-state objective optimization can be guaranteed. The theoretical results are demonstrated and discussed using a distillation tower as the model. Theoretical analysis and simulation results show that this control stratek--v is efl$cient and provides a good strategic solution to uractical urocess control.     

基于依赖关系的供应链优化协调

为提升供应链的整体绩效,设计适当的协调机制,使局部决策与整体目标相一致,基于协调理论,提出了资源共享、物流和时序三类供应链依赖关系,并通过相关的供应链优化模型将三类依赖关系形式化为关联约束。利用供应链模型的加可分性结构,基于拉格朗日松弛技术和次梯度算法构造一种优化协调机制,该协调机制通过松弛关联约束将模型分解为成员独立的子问题,并通过次梯度算法迭代更新拉格朗日乘子以协调成员局部决策。此外,相应于次梯度算法的实现方式,提出两种分布协调结构。     

环流问题过程瓶颈分析

网络流模型是CIMS是一种重要模型，基于网络流模型的瓶颈分析对于CIMS的分析和优化具有重要意义。环流问题实质是一种带增益的一般网络最大流问题，它要求特定的源点和汇点的流量成一定的比例关系，环流问题和一般环流问题构成了一般网络流量分析问题。本文通过瓶颈结构的定义对环流问题的增广路径进行了分解，并定义了子路径流的增广瓶颈，最后对环流问题的分析综合完成了瓶颈分析，并给出了一个算例。     

具有模糊缺陷率和订货费用的库存管理研究

为解决目前库存研究中忽略产品缺陷率和订货费用不确定的问题，研究了同时具有模糊缺陷率和模糊订货费用的库存管理问题。首先利用模糊理论描述了库存管理中的不确定性，建立了缺陷率和订货费用模糊下的经济订货批量模型，以确定合理的订货批量，使得整个利润最大。然后利用符号距离法对模型目标进行了解模糊运算，给出并证明了参数为三角形模糊数时的最优订货策略。最后利用仿真实验验证了该策略，并研究分析了缺陷率和订货费用的模糊性对最优订货批量和最优利润的影响。     

全面了解ODBC技术

开放式数据库互连技术在数据管理上可谓是数据库之间的桥梁,使得一个个小数据库连成了一个大的数据库,共享了信息资源。