基于区间控制的约束预测控制及约束影响

在实际被控过程中往往存在着很多约束条件,这使得预测控制的在线优化问题表现为非线性,难以获得控制律的具体表达式,为约束预测控制的分析造成困难基于Newton控制框架,针对线性系统离散状态空间的动态模型,考虑具有输入、输出区间约束条件下,基于区间控制思想的预测控制律的解析表达式,分别得到无约束和有约束情况下状态反馈控制律的...     

球罐液位实验装置的预测控制

预测控制是近年来发展起来的一类新型计算机控制算法。预测模型、滚动优化、反馈纠正适用于控制数学模型不易建立、且比较复杂的工业生产过程。针对球罐液位控制这一非线性系统，提出一种预测模型控制算法，使实际对象的动态响应品质获得有效的改善，得到了良好的控制效果。     

复杂工业过程的满意控制

本文从分析了工业过程优化控制的环境出发，针对复杂工业过程的特点与用户要求提出了满意控制的概念，给出了满意控制的基本框架，分析了它对复杂工业环境的适应性。     

连铸结晶器液位预测控制

提出一种能克服有色噪声扰动的广义预测控制方法,并将其用于结晶器液位控制中,结果表明液位偏差较小,系统鲁棒性大大改善。     

免疫遗传算法在过程A3000系统液位控制中的应用

以过程控制A3000系统作为载体,利用免疫遗传算法对PID参数进行优化,将得到的优化控制参数应用到液位控制中,通过实际系统的调试运行,得到了良好的控制效果,证明了该理论的可行性,从而提高了控制参数调节的速度,避免了参数调节的盲目性。     

基于RBF-ARX模型的预测控制在液位系统中的应用

针对单容液位系统紊流时的非线性特征,研究了基于RBF-ARX模型预测控制策略控制单容液位系统;讨论RBF-ARX模型结构的选取,模型参数辨识,RBF参数优化,基于RBF-ARX模型的预测控制策略等问题;模型的仿真结果,证实了RBF-ARX模型在非线性系统建模和辨识中的有效性;同基于全局线性ARX模型的预测控制器和PID控制器相比较,基于此模型的预测控制取得了优异的控制效果。     

一类工业过程运行反馈优化控制方法

为了克服流程工业运行优化中控制回路闭环系统的动态误差对运行优化性能的影响,本文针 对一类工业过程提出了使运行指标实际值与目标值偏差和控制回路输出与设定值跟踪误差的二次性能 指标极小化的运行优化反馈控制方法. 该方法由运行层设定值反馈控制和回路控制层设定值跟踪控制组成,其中设定值反馈控制采用基于LMI的 模型预测控制,回路控制采用衰减率可调的带有积分项的状态反馈调节律. 本文给出了保证运行优化反馈控制闭环系统渐近稳定的充分条件,并开展了浮选过程运行优化反馈控制仿 真实验,实验结果表明所提方法的有效性.     

大时滞过程的预测控制——催化裂化反应再生系统原料预热回路控制

实际的复杂工业过程,往往具有大的时滞,例如：炼油厂催化裂化装置的反应再生系统,其原料油预热通过油浆换热实现,因此时滞特别大,本文针对这一类大的时滞过程,设计了以动态矩阵控制为核心算法的预测控制系统,运行实践表明：这一控制方案比原ＰＩＤ控制在控制质量上有效大提高。     

工业过程系统的预测控制

预测控制方法自1970's提出后在学术界和工业应用领域都取得了很大的进展,尤其在工业过程控制方面成为一种重要的先进控制方法.根据工业过程控制的特点和进一步的需求,对近年来在工业过程控制领域预测控制方法取得的新进展进行综述,包括过程控制系统模型辩识,数据驱动的预测控制和在网络信息模式下的预测控制等.并对预测控制进一步的发展需求进行分析,介绍了欧盟正在进行的第七框架对于大系统分布式预测控制的研究内容.     

复杂工业过程的预测控制理论及其应用

文章针对复杂工业过程的特点,对近年来预测控制的理论研究及其应用进展进行了全面细致的综述,并指出了未来的研究方向。     

Stabilizing model predictive control: On the enlargement of the terminal set

It is well known that a large terminal set leads to a large region where the model predictive control problem is feasible without the need for a long prediction horizon. This paper proposes a new method for the enlargement of the terminal set. Different from existing approaches, the method uses the convex hull of trajectories as the basis for the construction. These trajectories may be any feasible trajectories of the system terminating in an invariant set that contains the origin and are not restricted to consist of equilibrium points only. The resulting terminal controller is the solution of an optimization problem depending on the state and is therefore in general a nonlinear function. Copyright © 2014 John Wiley & Sons, Ltd.     

通讯信息约束下具有全局稳定性的分布式系统预测控制

本文针对一类由状态相互耦合的子系统组成的分布式系统, 提出了一种可以处理输入约束的保证稳定性的非 迭代协调分布式预测控制方法(distributed model predictive control, DMPC). 该方法中, 每个控制器在求解控制率时只与 其它控制器通信一次来满足系统对通信负荷限制; 同时, 通过优化全局性能指标来提高优化性能. 另外, 该方法在优化 问题中加入了一致性约束来限制关联子系统的估计状态与当前时刻更新的状态之间的偏差, 进而保证各子系统优化问 题初始可行时, 后续时刻相继可行. 在此基础上, 通过加入终端约束来保证闭环系统渐进稳定. 该方法能够在使用较少 的通信和计算负荷情况下, 提高系统优化性能. 即使对于强耦合系统同样能够保证优化问题的递推可行性和闭环系统的 渐进稳定性. 仿真结果验证了本文所提出方法的有效性.     

锅炉汽包水位非自衡系统的预测控制

由于动态矩阵控制预测控制算法无法直接控制带有积分环节的过程,针对这一困难,研究了一种适用于积分过程的DMC算法.该算法通过改变经典DMC算法的移位阵,使得有限维阶跃响应系数模型能够对积分过程进行准确的未来输出预测,从而避免了预测截断误差的产生.锅炉汽包水位系统的工业实验结果验证了算法的有效性.由于算法的结构没有改变,计算量也没有增加,该算法较之已有的针对非自衡对象的算法有更强的实用性.     

Necessary and sufficient conditions for constraint satisfaction in switched systems using switch‐robust control invariant sets

This paper studies the control of constrained systems whose dynamics and constraints switch between a finite set of modes over time according to an exogenous input signal. We define a new type of control invariant sets for switched constrained systems, called switch–robust control invariant (switch‐RCI) sets, that are robust to unknown mode switching and exploit available information on minimum dwell‐time and admissible mode transitions. These switch‐RCI sets are used to derive novel necessary and sufficient conditions for the existence of a control‐law that guarantees constraint satisfaction in the presence of unknown mode switching with known minimum dwell‐time. The switch‐RCI sets are also used to design a recursively feasible model predictive controller (MPC) that enforces closed‐loop constraint satisfaction for switched constrained systems. We show that our controller is nonconservative in the sense that it enforces constraints on the largest possible domain, ie, constraints can be recursively satisfied if and only if our controller is feasible. The MPC and switch‐RCI sets are demonstrated on a vehicle lane‐changing case study.     

Decentralized control of the Tennessee Eastman Challenge Process

A decentralized control system is developed for the Tennessee Eastman Challenge Process (TE problem). The design procedure begins with the selection of the method for production-rate control, to which inventory controls and other functions are then coordinated. Results show that production rate can be maximized at any of the three standard product compositions, even when the feed of reactant A is lost. All specifications of the challenge problem are satisfied despite large disturbances in feed composition and reaction kinetics. Variability in product rate and quality is less than that seen in previous studies. The process can operate on-spec for long periods without feedback from composition measurements. Setpoints for certain variables (such as reactor temperature and concentrations of A and C in the reactor feed) must be chosen a priori, and the effect on operating cost is estimated. The performance of the proposed decentralized control is compared to that of a nonlinear model predictive control (NMPC) developed previously. There appears to be little, if any, advantage to the use of NMPC in this application. In particular, the decentralized strategy does a better job of handling constraints - an area in which NMPC is reputed to excel. Reasons for this are discussed.     

先进控制在环管聚丙烯装置上的应用

针对Himont工艺的大型聚丙烯工业装置质量指标实时控制的复杂性,本文提出了一种通过表观能量平衡反推物料平衡并结合经验数据回归的质量指标实时推断方法。利用基于闭环辨识的鲁棒内模控制方法实现了的大型聚丙烯工业装置的先进控制。所提先进控制解决方案已成功应用于某炼油厂的聚丙烯工业装置,长周期的运行结果证实了所提解决方案可以有效地减少产品质量波动,提高产率并减轻操作人员的工作强度,取得了显著的经济效益。     

Model predictive control for tracking randomly varying references

This paper proposes a model predictive control scheme for tracking a-priori unknown references varying in a wide range and analyses its performance. It is usual to assume that the reference eventually converges to a constant in which case convergence to zero of the tracking error can be established. In this note we remove this simplifying assumption and characterise the set to which the tracking error converges and the associated region of convergence.     

多变量解耦控制的工业过程运行层次控制方法

基于多变量解耦控制技术,提出了一种工业过程运行的层次控制方法,用于实现表征过程整体运行性能的工艺指标.底层回路控制系统采用多回路PI/PID控制技术进行设计,用于将关键工艺参数控制在给定的工作点.针对中被控过程和底层回路控制系统构成的文义对象,采用扩展的单位反馈解耦方法设计上层回路设定控制器,该回路设定控制器能够克服系...     

蜡油催化裂化装置的先进控制应用策略

详细论述了催化裂化装置的控制策略,利用先进控制的模型预估控制功能,提高装置的平稳程度,多变量预估控制的应用可以减少MV变量的变化,同时保证CV变量的平稳,主要表现在温度、液位和产品质量的平稳上;提高装置处理量和掺渣量及高价值产品收率;实现产品质量卡边控制：包括汽油干点、柴油95％点、稳定汽油RVP等;降低能耗：主要是降低泵负荷以及蒸汽的消耗。实现催化裂化反应再生系统、主分馏塔和吸收稳定系统的前馈控制和动态解藕．提高了对装置的控制水平。镇海300万吨／年催化裂化联合装置的先进控制经过一年多的投用,降低了关键变量的波动方差,得到了操作人员的欢迎．由于先进控制与工艺的密切关系,随着工艺改造和生产方案的变化,周期性地对先进控制的维护是用好先进控制的基础,加大了用好先进控制的难度。     

Interactions between control and process design under economic model predictive control

Economic model predictive control (EMPC) is a model-based control scheme that integrates process control and economic optimization, which can potentially allow for time-varying operating policies to maximize economic performance. The manner in which an EMPC operates a process to optimize economics depends on the process dynamics, which are fixed by the process design. This raises the question of how process and EMPC designs interact. Works which have addressed process and control design interactions for steady-state operation have sought to simultaneously develop process designs and control law parameters to find the most profitable way to operate a process that is able to prevent process constraints from being violated and to optimize capital costs in the presence of disturbances. Because EMPC has the potential to operate a process in a transient fashion, this work first focuses on how EMPC and process design interact in the absence of disturbances. Using small-scale process examples, we seek to understand the fundamental nature of the interactions between EMPC and process design, including how these interactions can impact computational complexity of the controller and the design procedure. We subsequently utilize the insights gained to suggest controller design variables which might be considered as decision variables for a simultaneous process and control design problem when disturbances are considered.