典型振荡过程动态矩阵控制的性能分析

基于动态矩阵控制的闭环传递函数,研究了典型振荡过程在动态矩阵控制下的系统性能,给出了主要设计参数与系统稳定性、动态响应的若干重要关系,提供了分析此类系统的理论基础.     

预测控制的无扰切换技术

提出了关于动态矩阵控制器(DMC)与广义预测控制器(GPC)的改进无扰切换方法．其中 ，前者在DMC控制模式启动初期采用过程的脉冲响应模型实现对过程输出的自由响应预测， 在非DMC控制模式下，只需要存储过程输入/输出数据，而不必在线进行反馈校正．二者都有 一个共同特点，即不必考虑过程的直流工作点，这给预测控制算法的在线实现带来了很大的 方便．最后，通过纸机定量控制系统的仿真研究证明了上述算法的有效性．     

麦汁冷却过程的动态矩阵控制

针对啤酒糖化中的麦汁冷却过程随负荷工况变化而表现出来的参数不确定性，运用动态控制矩阵理论设计控制器，并在自行研制的AUTO-2000集散型控制系统中实现，实验结果表明，该控制器的补偿效果优于PID控制。     

工业生产过程中的SCADA应用分析

在分析数据采集与监视控制系统(SCADA)结构的基础上,通过文字和图表清晰的描绘出了SCADA在工业生产中的控制原理,并深入剖析了SCADA在生产过程控制中的功能与应用.     

一种具有PID结构的动态矩阵控制

动态矩阵控制（DMC）是基于对象阶跃响应的一种预测控制算法，它具有结构清晰、算法简单、对模型失配适应能力强等优点，适用于纯时滞，开环渐近稳定的线性对象，是一种成功而有效的控制算法。但DMC的输出动态特性受其参数的影响，目前，对DMC参数的选取一般都是采用试凑结合仿真的方法，费时又费力，从而给设计者造成很大的困难。该文提出了一种对DMC的改进方法——DMPIDC，使PID参数整定方法与动态矩阵控制结合起来．用整定出的PID参数作为DMPIDC的加权系数，保证了良好的输出动态特性，仿真结果表明这种方法是可行的。     

煮糖结晶过程的多模型动态矩阵控制研究

由于工业结晶过程存在非线性和滞后现象,因此采用常规的控制策略已经达不到工业生产的要求。针对这种情况,通过对煮糖结晶过程的机理分析建立了反映实际煮糖过程的动态模型,在此基础上采用一种先进的预测控制算法即多模型非线性动态矩阵控制(DMC)算法进行控制。仿真和对比研究有力地证明了所建立的模型是有效的,同时也证明该算法可以应用到工业结晶过程弗能够取得较好的控制品质。     

不稳定对象的动态矩阵控制

1引言70年代中期发展起来的各种预测控制算法，如动态矩阵控制（DMC）［‘1，模型算法控制（MAC）［’j等，由于采用了简易的建模方式，以滚动优化和在线误差校正保证了优良的控制性能和对参数、环境变化的强鲁棒性，已在工业过程中获得了广泛应用。因为这些算法是基于线性对象的有限阶跃或脉冲响应等非参数模型，所以它们只适用于渐近稳定的线性对象，不能直接用于带积分环节的非自衡系统和不稳定的被控对象［”‘j与非参数模型相反，Clarke［’j等提出的基于CARIMA模型的广义预测控制（GPC）算法，结合了辨识和自校正机制。据说能…     

时滞切换系统动态反馈H∞控制

对于由若干线性时滞子系统构成的切换系统,考虑了动态反馈控制与切换策略的设计,以实现H∞性能的优化．利用其连续性不受切换行为影响的Lyapunov-Krasovskii泛函构造方式,并结合闭环子系统的适当变换,导出了与时滞相关的控制器及切换策略的存在性判据．通过参数代换与矩阵相似变换,将此判据等价地转化为线性矩阵不等式,从而解得泛函与控制器参数．仿真结果验证了方法的有效性．     

基于动态模型库的多模型切换控制

针对含有有界扰动和模型参数跳变的离散时间系统,提出基于动态模型库的多模型切换控制方法.在模型参数范围未知情况下,利用在线学习的多模型自适应控制算法自动建立多模型,并对模型库中的子模型进行优化.采用具有积分特性的指标函数作为切换准则.在每一采样时刻根据其最小值来选择与实际系统最接近的模型,并将基于此模型的控制器切换为当前控制器.文中证明了该算法能够保证闭环系统的稳定性和跟踪误差的渐近收敛性.计算机仿真结果表明该算法的有效性.     

Filter-based iterative learning control for linear large-scale industrial processes

In the procedure of the steady-state hierarchical optimization with feedback for large-scale industrial processes, a sequence of set-point changes with different magnitudes is carried out on the optimization layer. To improve the dynamic performance of transient response driven by the set-point changes, a filter-based iterative leaning control strategy is proposed. In the proposed updating law, a local-symmetric-integral operator is adopted for eliminating the measurement noise of output information, a set of desired trajectories are specified according to the set-point changes sequence, the current control input is iteratively achieved by utilizing smoothed output error to modify its control input at previous iteration, to which the amplified coefficients related to the different magnitudes of set-point changes are introduced. The convergence of the algorithm is conducted by incorporating frequency-domain technique into time-domain analysis. Numerical simulation demonstrates the effectiveness of the proposed strategy.     

The application of fuzzy control systems to industrial processes

The paper describes the application of fuzzy algorithms to the control of dynamic processes. The fuzzy control algorithm is used to implement linguistically expressed heuristic control policies directly, with a view to automating those complex and poorly-defined processes where modelling difficulties and lack of suitable measurements make manual control imperative. The results obtained from two pilot-scale studies are presented and the stability of the fuzzy control system is discussed.     

广义稳态的工业过程及其优化控制

阐述了工业过程中出现的拟周期和混沌等动态行为，并分析了形成的原因和条件．介绍了与之密切相关的非线性科学中的混沌、微分动力学系统以及遍历论等理论，综述了工业过程的广义稳态优化控制的研究成果、理论意义和实用价值及其发展方向．     

工业过程稳态优化进程中的噪声平滑型迭代学习控制

针对具有噪声的工业过程稳态优化进程，提出迭代学习控制以期改善控制系统的动态品质，建立了基本的加权噪声平滑型迭代学习控制算法结构。利用频域时域相结合的方法分析和论证了算法的收敛性，给出噪声平滑参数的确定策略，数字仿真表明，平滑型迭代学习控制算法能有效消除噪声对系统输出信号的影响，显著改善工业过程稳态优化进程中控制系统的动态品质。     

Advanced methods of process computer control for industrial processes

In recent years, the requirements for the performance of multilevel process control, including feedforward and feedback control, monitoring and optimization have increased. Applying process computers and micro computers, the functions of analog equipment and hardwired logic devices cannot only be replaced. Extended or quite new methods can be realized improving the performance of multilevel process control. These advanced methods for process control are characterized by: more sophisticated, better adjusted control algorithms, forecasting of process variables, estimation of not directly measurable variables, computer aided design of algorithms and adaptive or selftuning algorithms. The basis of these advanced methods are mathematical models of the processes and their signals, often gained by the process computer itself during on-line operation.The present paper discusses first how process models in open and closed loop can be obtained by on-line identification methods. Then, based on these models, the computer aided design of control algorithms, adaptive control algorithms and adaptive steady-state on-line optimization will be regarded. Monitoring of not direct measurable variables will be mentioned. For some methods, practical results with real and simulated processes are shown. Interactive process computer software packages are used which can easily be transferred to other process computers.     

工业自动化控制系统的设计

工业生产过程自动化系统经过长期不断的发展,特别是在充分利用计算机技术的基础上取得了很大的进步,在生产过程中已发挥其重要作用,成为生产过程安全、稳定、自动化运行不可缺少的工具。本文从工业生产自动化现状趋势、生产过程自动化系统和生产管理系统、软PLC和软DCS、生产过程控制和管理软件的融合等方面展开论述．从工业生产与自动化控制融合环节提出工业自动化控制系统设计的独特见解。     

工业自动化控制系统的设计

工业生产过程自动化系统经过长期不断的发展,特别是在充分利用计算机技术的基础上取得了很大的进步,在生产过程中已发挥其重要作用,成为生产过程安全、稳定、自动化运行不可缺少的工具。本文从工业生产自动化现状趋势、生产过程自动化系统和生产管理系统、软PLC和软DCS、生产过程控制和管理软件的融合等方面展开论述,从工业生产与自动化控制融合环节提出工业自动化控制系统设计的独特见解。     

含扩散项不可靠生产系统最优生产控制的数值求解

针对含扩散项不可靠随机生产系统最优生产控制的优化命题, 采用数值解方法来求解该优化命题最优控制所满足的模态耦合的非线性偏微分HJB方程. 首先构造Markov链来近似生产系统状态演化, 并基于局部一致性原理, 把求解连续时间随机控制问题转化为求解离散时间的Markov决策过程问题, 然后采用数值迭代和策略迭代算法来实现最优控制数值求解过程. 文末仿真结果验证了该方法的正确性和有效性.     

Online monitoring of nonlinear multivariate industrial processes using filtering KICA–PCA

In this paper, a novel approach for processes monitoring, termed as filtering kernel independent component analysis–principal component analysis (FKICA–PCA), is developed. In FKICA–PCA, first, a method to calculate the variance of independent component is proposed, which is significant to make Gaussian features and non-Gaussian features comparable and to select dominant components legitimately; second, Genetic Algorithm is used to determine the kernel parameter through minimizing false alarm rate and maximizing detection rate; furthermore, exponentially weighted moving average (EWMA) scheme is used to filter the monitoring indices of KICA–PCA to improve monitoring performance. In addition, a novel contribution analysis scheme is developed for FKICA–PCA to diagnosis faults. The feasibility and effectiveness of the proposed method are validated on the Tennessee Eastman (TE) process.     

Measurement,control and simulation of an industrial liquid-liquid extractor

This brief paper presents a study conducted on an industrial liquid-liquid extractor which had been operated with lower throughput rates than the design to meet the product specifications. The study showed that a certain amount of the aqueous phase holdup should exist at one section of the extractor to carry out the required mass transfer. This fact had been thought of neither at the extractor design stage nor after a few years' operation experience. Differential equations representing the holdup dynamics were developed and an on-line measurement and control system was designed to maintain the holdup constant.