不确定离散线性切换系统的鲁棒控制

利用共同李亚普诺夫函数方法和线性矩阵不等式处理方法,研究了一类含有结构参数不确定性的离散时间切换系统的鲁棒渐近稳定问题。基于凸组合条件,通过各个子系统的状态反馈控制器和相应切换规律的设计,在有限控制器之间进行切换使得该系统是全局渐近稳定的。文中用数学方法证明了该设计方法的有效性,所得结果为线性切换系统的分析提供了更深的视角,有助于控制系统其它性能实现。     

Economic model predictive control of nonlinear process systems using empirical models

Economic model predictive control (EMPC) is a feedback control technique that attempts to tightly integrate economic optimization and feedback control since it is a predictive control scheme that is formulated with an objective function representing the process economics. As its name implies, EMPC requires the availability of a dynamic model to compute its control actions and such a model may be obtained either through application of first principles or through system identification techniques. In industrial practice, it may be difficult in general to obtain an accurate first‐principles model of the process. Motivated by this, in the present work, Lyapunov‐based EMPC (LEMPC) is designed with a linear empirical model that allows for closed‐loop stability guarantees in the context of nonlinear chemical processes. Specifically, when the linear model provides a sufficient degree of accuracy in the region where time varying economically optimal operation is considered, conditions for closed‐loop stability under the LEMPC scheme based on the empirical model are derived. The LEMPC scheme is applied to a chemical process example to demonstrate its closed‐loop stability and performance properties as well as significant computational advantages. © 2014 American Institute of Chemical Engineers AIChE J, 61: 816–830, 2015     

质量工具在PVC过程质量管理中的应用

基于质量工具软件,运用统计过程控制、过程能力分析技术对PVC树脂生产过程的质量进行预防控制,并分析判断产生降级品的原因,确保过程可控且满足工序质量要求.通过对生产过程中的质量控制和改进来提高指标达标率.以具体应用案例说明统计过程质量控制、过程能力分析应用技术的实施方法及效果,表明质量工具软件在持续提高PVC树脂过程质量...     

执行器饱和受限约束下锅炉燃烧系统的鲁棒预测控制

针对执行器饱和受限锅炉燃烧系统,提出一种鲁棒预测控制方法。首先,建立燃烧过程的线性参数变化系统模型,将执行器饱和受限转变成凸包形式描述;进而,设计执行器饱和受限的鲁棒预测控制器;最后,以某电站300MW机组锅炉控制为实例,对所提出的方法进行验证。结果表明:该方法可以在满足执行器饱和受限约束的同时获得满意的性能。     

变工况切换过程的Petri网自主预测与控制

针对变工况切换过程中切换点难以确定且切换准则不完善等问题,以大范围升温过程为例,利用仿人智能控制中"全压-零制动-稳态调节"的控制策略,提出了"预测Petri网",即在Petri网中增加预测器,为Petri网的变迁提供了判断元素。根据"预测-决策-再预测-再决策"的思想,增加切换过程的判断条件,实现了Petri网自主寻优过程。最后在实验室电加热炉装置上实验表明,在切换点不确定的情况下,在线寻找到切换点并增加了切换条件,使系统的切换更为平稳光滑,提升了系统响应速度和稳定性。     

化工过程多回路PID控制系统模式切换参数自整定

化工过程一般为多变量系统,但其主要控制方案为分散多回路PID常规控制。由于多变量系统内部存在不同程度的耦合作用,各控制回路之间存在相互影响,当其他回路进行手动/自动模式切换时,本回路等效被控对象将会发生突变,导致本回路的原有控制参数不能适应等效被控对象的变化,造成控制性能下降,甚至闭环系统不稳定。为避免这种情况的发生,从整个系统的角度研究控制回路模式切换时的稳定性,采用多变量频域Nyquist阵列设计法。基于对角优势下正Nyquist稳定性判据,从Gershgorin圆边界点的角度定量分析各个控制回路在模式切换前后的稳定性变化程度,从而确定各回路控制器增益的调整方向及程度,实现各回路的控制器参数在控制回路模式切换瞬间的自动整定,尽可能抵消控制回路模式切换对整个系统的扰动,保证整个系统的闭环稳定性。以Shell公司重油分馏塔的多回路PID控制系统为例,将3个PID控制回路依次投用时,根据Gershgorin圆边界点进行控制参数的自整定,闭环系统仍能保持一定的控制性能,否则闭环系统将不稳定。     

基于图模型的间歇过程误操作风险辨识

提出了一套基于图模型的建模方法,该模型以Petri网和符号有向图（SDG）为基础将模型分为上部和下部,加入操作点、控制库所、判断模块等模型元素,并结合间歇过程的特点,提出了关联变量、目标变量检查表、操作点检查表和关联变量检查表等概念。根据误开误关、过早过晚、步骤添加删除等误操作,对模型进行验证。验证结果表明,该模型解决了先前方法难以描述具体操作的缺陷,并且模型结构简单,具有整体性。不仅能够方便地描述3种不同类型的误操作,还能有效地对误操作进行风险辨识,具有一定的适用性。     

基于特征样本核主元分析的TE过程快速故障辨识方法

核主元分析（KPCA）在非线性系统的故障检测方面明显优于普通的PCA方法,但存在无法进行故障辨识以及在故障诊断过程常常出现核矩阵K计算困难等难题。针对上述问题,提出了一种基于特征样本核主元分析方法（FS-KPCA）非线性故障辨识方法。首先采用特征样本（FS）提取方法有效解决核矩阵K的计算量问题。然后利用计算核函数的偏导方法求取KPCA监控中每个原始变量对统计量T²和SPE的贡献率,利用每个变量对监控统计量贡献程度的不同,可以辨识出故障源。将上述方法应用到TE过程,仿真结果表明该方法不仅能够有效辨识故障,而且提高了故障检测和辨识速度。     

Making use of process tomography data for multivariate statistical process control

A novel strategy for making effective use of on‐line process tomography measurements for process monitoring is described. The electrical resistance tomography (ERT) sensing system equipped with sixteen electrodes provides 104 conductivity measurements every 25 ms. The data has traditionally been used for construction of images for display purpose. In this study, ERT data was used for multivariate statistical process control. Data at predefined normal operational conditions was processed using principal component analysis. The compressed data was used to derive two statistics, T² and squared prediction error (SPE). T² and SPE charts predict the probability that the process being monitored has undergone statistically significant changes from previous state or the so‐called normal operational state, in terms of mixing quality. The methodology is illustrated by reference to a case study of a sunflower oil/water emulsion process. © 2010 American Institute of Chemical Engineers AIChE J, 2011     

On identification of well‐conditioned nonlinear systems: Application to economic model predictive control of nonlinear processes

The focus of this work is on economic model predictive control (EMPC) that utilizes well‐conditioned polynomial nonlinear state‐space (PNLSS) models for processes with nonlinear dynamics. Specifically, the article initially addresses the development of a nonlinear system identification technique for a broad class of nonlinear processes which leads to the construction of PNLSS dynamic models which are well‐conditioned over a broad region of process operation in the sense that they can be correctly integrated in real‐time using explicit numerical integration methods via time steps that are significantly larger than the ones required by nonlinear state‐space models identified via existing techniques. Working within the framework of PNLSS models, additional constraints are imposed in the identification procedure to ensure well‐conditioning of the identified nonlinear dynamic models. This development is key because it enables the design of Lyapunov‐based EMPC (LEMPC) systems for nonlinear processes using the well‐conditioned nonlinear models that can be readily implemented in real‐time as the computational burden required to compute the control actions within the process sampling period is reduced. A stability analysis for this LEMPC design is provided that guarantees closed‐loop stability of a process under certain conditions when an LEMPC based on a nonlinear empirical model is used. Finally, a classical chemical reactor example demonstrates both the system identification and LEMPC design techniques, and the significant advantages in terms of computation time reduction in LEMPC calculations when using the nonlinear empirical model. © 2015 American Institute of Chemical Engineers AIChE J, 61: 3353–3373, 2015     

模式切换类经济预测控制切换时间在线估计

针对一类非线性仿射系统,提出一种在线估计切换时间的经济模型预测控制算法,并将其拓展到长周期控制过程中。有限时间内,将切换时间作为变量实时更新估计,确定最优的切换操作点,以保证每一时刻都可以在控制目标可达的前提下经济性能最优,避免了传统切换经济预测控制策略可能出现的控制目标不可达或经济性能较差的情况。进一步,将该策略作为单周期应用到长周期优化控制过程中,当系统受到扰动时,开始一个新的优化控制周期,实现优化模式与控制模式的灵活切换,同时可以及时应对扰动的出现。该策略保证系统的综合性能最优,仿真结果证明了方法的有效性。     

SPC在汽车用阻尼板质量控制过程中的应用

汽车用阻尼板的主要功能是抑制车身结构共振,降低车内噪声,生产过程中的质量控制是非常重要的,应用SPC监控生产过程,要正确选择控制变量,本文探讨了控制变量的选择及其应用。     

Robust fault detection and monitoring of hybrid process systems with uncertain mode transitions

A methodology for fault detection and monitoring of a class of hybrid process systems modeled by switched nonlinear systems with control actuator faults, uncertain continuous dynamics, and uncertain mode transitions is presented. A robust hybrid monitoring scheme that distinguishes reliably between faults, mode transitions, and uncertainty is developed using tools from unknown input observer theory and results from Lyapunov stability theory. The monitoring scheme consists of (1) a family of dedicated mode observers that locate the active operating mode at any given time and detect mode switches, (2) a family of robust Lyapunov‐based fault detection schemes that detect the faults within the continuous modes, and (3) a supervisor that synchronizes the switching between different controllers and different fault detectors as the process transitions from one mode to another. A key idea of the developed framework is to design the mode observers in a way that facilitates the identification of the active mode without information from the controllers and renders the residuals insensitive to the faults and uncertainties in the constituent subsystems. The implementation of the developed monitoring scheme is demonstrated using a simulated model of a chemical reactor that switches between multiple operating modes. © 2010 American Institute of Chemical Engineers AIChE J, 2011     

以氧化还原电位作为缺氧-好氧法工艺反硝化反应模糊控制的参数

以淀粉废水为研究对象,重点研究了氧化还原电位(ORP)作为缺氧-好氧法(A/O)工艺反硝化反应模糊控制参数的可行性,研究表明缺氧区末端硝酸氮浓度与ORP值具有很好的相关性,可以作为A/O工艺内循环回流量和外碳源投加的模糊控制参数,并建立了ORP模糊控制器。单独控制内循环回流量维持反硝化区末端ORP值为(-86±2)mV,或单独控制外碳源投加量维持反硝化区末端ORP值为(-90±2)mV,可实现A/O工艺脱氮的最优控制。     

The integration of spectroscopic and process data for enhanced process performance monitoring

Batch process performance monitoring has been achieved primarily using process measurements with the extracted information being associated with the physical parameters of the process. With increasing attention now being paid to the application of on‐line real‐time process analytics through spectrometry, together with the FDA Process Analytical Technologies (PAT) initiative, the use of spectroscopic information for enhanced monitoring of reactions is gaining impetus. The harmonious integration of process data and spectroscopic data then becomes a major challenge. By integrating the process and spectroscopic measurements for multivariate statistical data modelling and analysis, it is conjectured that improved process understanding and fault diagnosis can be achieved. An investigation into combining process and spectral data using multiblock and multiresolution analysis is proposed and the results from the analysis of experimental data from two industrial application studies are presented to demonstrate the improvements achievable in terms of process performance monitoring and fault diagnosis.     

催化裂化装置反再系统动态模拟精细化与控制系统“工艺优先”配对设计

催化裂化是目前炼油厂中的核心加工工艺,其反应-再生系统是一个多变量紧密耦合的复杂系统,动态模拟和控制系统设计难度较大。目前,催化裂化装置在进行动态建模时设置了大量假设条件,与实际状况存在诸多不符,另外当前的控制回路配对方法未考虑工艺要求,也不适用于催化裂化这样的开环不稳定系统。基于以上原因,以已建立的反应-再生系统数学模型为基础,建立精细化动态模型,对反应器和再生器模型进行真实逼近,不再忽略气相动态变化,将原模型中气相对时间的导数项恢复,通过离散化的分布参数系统模型,对离散化模型中每段提升管和烧焦罐的时变变量加入时滞。仿真结果表明,精细化动态模型更加接近实际化工生产过程。根据上述模型搭建仿真平台,通过对不稳定的反再系统进行工艺优先的控制系统设计,首先根据化工工艺设计控制回路保证系统的稳定性,然后基于相对增益阵方法设计剩余变量配对,在降低了高维系统设计复杂度的同时保证了生产过程安全。设计结果表明,对于催化裂化装置反再系统,基于工艺特性完成控制回路配对后,剩余变量无须再添加多余的控制回路就能保证控制系统的稳定性和适当的控制性能。     

PVC生产过程优化控制系统工程

介绍了以计算机、DCS为核心设备,以网络为信息平台,把PVC生产过程中工业优化过程控制和优化生产管理结合,构建PVC生产过程优化控制系统工程的情况。     

DCS模数转换器字长对炼油化工过程控制性能的影响

深入分析现场模拟信号离散化过程中误差的产生机制，离散误差是由采样器的采样周期和A／D转换器的字长分别引起并迭加而成，二者分别在时间轴和信号轴上产生，不能互相补偿，而DCS生产厂家容易忽视后者在离散化中的重要性，针对炼油化工实际应用，建议DCS选型时，选择全部16位字长的转换器，且各信号量程可以单独设定。     

PTA装置氧化反应器自动升降负荷的先进控制

针对PTA装置氧化反应器升降负荷过程中存在的滞后大、动态响应慢、非线性严重、回路间关联性强等控制难点,在多变量预测控制器基础上设计了自动升降负荷系统,极大提高了生产操作平稳度,降低了物耗和能耗及产品质量的波动,取得良好的控制效果和显著的经济效益。     

ABS/PC回收再造粒的快速鉴定

通过观察丙烯腈－丁二烯－苯乙烯共聚物／聚碳酸酯（ABS／PC）共混树脂粒子断面有无孔洞，来鉴别其是否为回收再造粒，结果表明，ABS／PC回收再造后粒子断面出现的孔洞系ABS／PC中PC的高温条件下水解作用产生，且随回收再造次数的增多会使形成的孔洞数量增加，孔径增大，该鉴定方法简便，快速，准确，易于推广，在出入境检验检疫部门和海关执法检验中具有实际应用价值。