基于鲁棒模型优化的工艺设计与控制系统集成

采用一种基于鲁棒模型优化方法求解工艺设计与控制集成问题,其核心思想是采用参数不确定状态空间模型描述闭环系统的非线性行为,基于该模型以及二次李雅普诺夫函数可估计系统在外部扰动作用下过程变量变化的最大边界,同时也可测试系统的鲁棒稳定性。该方法避免了求解集成优化问题常用的动态优化方法,可将其转化成一个非线性规划问题。该方法应用于CSTR反应过程的集成优化设计中,结果表明在存在外部扰动时,不仅可以保证过程的经济性能和动态性能,也可保证系统的鲁棒稳定性。     

基于扩张状态观测器的换热器动态面控制

针对带有延时、大惯性换热器温度控制问题,设计基于扩张状态观测器（ESO）动态面控制器。换热器温度控制是非线性的、时变的和不确定的动态过程,采用扩张状态观测器不仅可以获取系统不可测状态还能实时估计系统动态;采用动态面控制律,实现对温度的精确快速跟踪。利用Lyapunov函数证明控制系统的稳定性。通过对经典PID控制方法、动态矩阵控制方法和基于扩张状态观测器的动态面控制方法进行比较,仿真结果表明基于扩张状态观测器的动态面控制方法具有更优越的控制效果和鲁棒性能,且在被控系统设定值和扰动发生变化时具有更好的动态响应性能。     

基于扩张状态观测器的换热器动态面控制

针对带有延时、大惯性换热器温度控制问题,设计基于扩张状态观测器(ESO)动态面控制器。换热器温度控制是非线性的、时变的和不确定的动态过程,采用扩张状态观测器不仅可以获取系统不可测状态还能实时估计系统动态;采用动态面控制律,实现对温度的精确快速跟踪。利用Lyapunov函数证明控制系统的稳定性。通过对经典PID控制方法、动态矩阵控制方法和基于扩张状态观测器的动态面控制方法进行比较,仿真结果表明基于扩张状态观测器的动态面控制方法具有更优越的控制效果和鲁棒性能,且在被控系统设定值和扰动发生变化时具有更好的动态响应性能。     

多故障并发不确定系统的鲁棒完整性容错控制

针对传统容错控制方法难以保证非线性系统在执行器和传感器多故障并发情形下的稳定性问题,研究了一类时滞不确定模糊系统的鲁棒完整性容错控制方法。建立了基于T-S模糊逻辑的不确定非线性模型,定义执行器和传感器故障阵的标准归一化形式,在利用Newton-Leibniz公式变换系统结构的基础上,根据线性矩阵不等式技术给出了鲁棒容错控制器存在的时滞相关性充分条件,以保证整个闭环系统在执行器和(或)传感器发生故障时的稳定性,同时满足给定的广义鲁棒性能约束,联合抑制扰动、初始状态和时滞状态对系统性能的影响。最后仿真结果验证了方法的必要性和可行性。     

初始状态不确定的非线性过程系统状态估计的鲁棒粒子滤波方法

在过程系统的控制与故障检测等方面,状态估计发挥着重要作用。针对非线性过程系统状态估计过程中初始状态不确定性问题,提出一种鲁棒粒子滤波方法。该方法首先引入初始状态准确性间接判定准则,根据判定的结果来选择是否进行基于观测偏差反馈机制的初始状态迭代改进。初始值准确性较差时,可以通过初始状态迭代改进策略使最终的初始粒子更接近真实的初始状态,从而增加产生初始粒子的正确性概率,通过粒子滤波迭代得到更准确的状态估计结果。将提出的鲁棒粒子滤波方法与传统粒子滤波方法应用于两个非线性动态系统实例中,结果验证了所提出方法的有效性与鲁棒性。     

一类不确定多时滞系统的鲁棒容错控制研究

讨论一类线性不确定多时滞系统的鲁棒容错控制问题.基于Lyapunov稳定性理论和线性矩阵不等式方法（LMI）,针对一类参数有界不确定多时滞系统,给出了状态反馈鲁棒容错控制器设计方法,并且利用该方法得到的闭环控制系统,不仅在执行器失效情况下具有渐进稳定性,对参数不确定也具有良好的鲁棒性.最后,应用设计实例及仿真结果验证该设计方法的可靠性和有效性.     

初始状态不确定的非线性过程系统状态估计的鲁棒粒子滤波方法

在过程系统的控制与故障检测等方面,状态估计发挥着重要作用。针对非线性过程系统状态估计过程中初始状态不确定性问题,提出一种鲁棒粒子滤波方法。该方法首先引入初始状态准确性间接判定准则,根据判定的结果来选择是否进行基于观测偏差反馈机制的初始状态迭代改进。初始值准确性较差时,可以通过初始状态迭代改进策略使最终的初始粒子更接近真实的初始状态,从而增加产生初始粒子的正确性概率,通过粒子滤波迭代得到更准确的状态估计结果。将提出的鲁棒粒子滤波方法与传统粒子滤波方法应用于两个非线性动态系统实例中,结果验证了所提出方法的有效性与鲁棒性。     

具有随机丢包的非线性网控系统的鲁棒H_∞故障检测

针对具有模型不确定性和状态时滞的非线性网控系统,对它具有随机丢包的鲁棒H∞故障检测问题进行研究。采用动态故障检测滤波器构造残差产生器,将鲁棒H∞故障检测问题转化成H∞滤波器设计问题。所设计的鲁棒故障检测滤波器保证了故障检测系统均方渐近稳定且具有特定的H∞性能指标γ。数值仿真结果表明:利用该方法能够迅速准确地检测出系统的故障信号。     

一类不匹配不确定动态系统的鲁棒执行器故障检测与重构

针对一类不匹配不确定性动态系统,将不匹配不确定性的滑模控制方法与线性矩阵不等式（LMI）方法结合,设计一种新的鲁棒滑模观测器,提出了不匹配不确定动态系统滑模观测器稳定的充分必要条件以及LMI的存在定理,并证明了对系统不确定性以及外界干扰具有鲁棒性。无须对动态系统进行规范化处理,直接利用LMI方法求解鲁棒观测器增益矩阵,简化了滑模观测器设计过程。根据上述设计的鲁棒滑模观测器,应用等价输出误差介入原理和LMI方法,设计重构执行器故障的优化策略,提出在线获取故障信息的鲁棒执行器故障检测与重构方法,实现执行器故障的检测与重构。数字仿真验证了执行器故障重构方法的可靠性。     

一类非线性不确定时滞系统鲁棒预测控制

针对一类非线性不确定时滞系统,结合Lyapunov稳定性定理和H∞理论,得到系统渐进稳定和状态反馈H∞控制器存在的充分条件,并且给出了此类非线性不确定时滞系统的鲁棒H∞状态反馈控制律设计方案.最后通过具体数值仿真说明了设计方案的有效性.     

A NEW APPROACH TO DECENTRALISED PROCESS CONTROL USING PASSIVITY AND SECTOR STABILITY CONDITIONS

A new robust decentralised process control strategy based on the sector stability theorem is proposed in this paper. The interaction between sub-systems is measured by a revised passivity index, which is used in the development of a new stability condition for decentralised control. The controller synthesis method is developed to satisfy the stability condition and H_∞ performance specification. The decentralised control of a boiler furnace is studied as an application example.     

基于微粒群优化的鲁棒PID控制器参数整定方法研究

针对复杂工业过程中存在的一类模型不确定问题,提出一种新的鲁棒PID控制器参数整定方法.通过将鲁棒PID控制器的参数整定问题转化成一个max-min优化问题,利用微粒群优化(PSO)的协作算法对之进行求解,能获得某种鲁棒性能指标最优的PID控制器.对连续搅拌反应釜系统的实例仿真结果表明:与其它典型鲁棒PID控制器设计方法相比,本方法得到的PID控制器具有更强的鲁棒性和抗干扰能力,当过程操作范围发生大的变化时,利用本方法设计的鲁棒PID控制器能获得满意的结果.     

A NEW APPROACH TO DECENTRALISED PROCESS CONTROL USING PASSIVITY AND SECTOR STABILITY CONDITIONS

A new robust decentralised process control strategy based on the sector stability theorem is proposed in this paper. The interaction between sub-systems is measured by a revised passivity index, which is used in the development of a new stability condition for decentralised control. The controller synthesis method is developed to satisfy the stability condition and H_∞ performance specification. The decentralised control of a boiler furnace is studied as an application example.     

Melt index prediction by weighted least squares support vector machines

Melt index is considered an important quality variable determining product specifications. Reliable prediction of melt index (MI) is crucial in quality control of practical propylene polymerization processes. In this paper a least squares support vector machines (LS‐SVM) soft‐sensor model of propylene polymerization process is developed to infer the MI of polypropylene from other process variables. Considering the use of a SSE cost function without regularization might lead to less robust estimates; the weighted least squares support vector machines (weighted LS‐SVM) approach of propylene polymerization process is further proposed to obtain a robust estimation of melt index. The performance of standard SVM model is taken as a basis of comparison. A detailed comparison research among the standard SVM, LS‐SVM, and weighted LS‐SVM models is carried out. The research results confirm the effectiveness of the presented methods. © 2006 Wiley Periodicals, Inc. J Appl Polym Sci 101: 285–289, 2006     

Control relevant on‐line model validation criterion based on robust stability conditions

This paper is concerned with detection and diagnosis of modelling error under closed‐loop conditions. The effect of modelling error on process output error (which is the error between the process output and the simulated output) is first analysed. Then robust stability conditions for on‐line model validation are applied. The main premise is that whenever the closed‐loop system violates the robust stability condition, it is a sign of significant process change and a signal that the control system may become potentially unstable. We relate the process output error with robust stability conditions and introduce three propositions for on‐line model validation. Any process change (or modelling error) that makes the system violate the condition specified by the robust stability theorem can be detected. Simulation examples are presented to demonstrate the applicability of the propositions. An index is also proposed to quantify modelling error in frequency domain. Simulation examples and an experimental case study are presented to demonstrate the use of the new index.     

随机重复过程的鲁棒L_2-L_∞动态输出反馈控制

应用Lyapunov函数及线性矩阵不等式技术研究了随机重复过程的鲁棒L2-L∞动态输出反馈控制问题,目的是设计一个全阶控制器使随机重复过程均方渐近稳定。给出鲁棒L2-L∞全阶控制器存在的充分条件,并将控制器的设计转化为一个凸优化的求解问题。所设计的控制器能够保证相对于所有能量有界的外界扰动信号,重复过程的L2-L∞性能指标小于一定值γ。仿真实例证实了该设计方法的有效性。     

Sample data proportional control comparison between half and zero-order hold

Design techniques are presented for choosing the loop gain and sampling time for feed-back proportional control of a sample data process with half-order hold. The response of a second order process with transport lag when controlled by an algorithm chosen by this technique was compared to that for a process with zero-order hold. The design technique may be used for a process of any order of complexity as long as it can be adequately modeled as a second order overdamped system with pure delay. The control algorithm was experimentally tested on a fourth-order heat transfer process which was modeled as a second-order overdamped process with pure delay. A new performance index was used in the design of the control parameters. Bother zero-order and half-order holds were tested experimentally and the controlled and manipulated variable responses were compared.     

Modeling and control of the melt index in HDPE process

We investigate the model for an industrial isothermal HDPE slurry reactor. The model, consisting of several nonlinear equations, can be linearized to give sets of linear time invariant state space model. The effectiveness of the linearized model is verified by the numerical simulations. A simple model predictive control scheme is constructed based on the linear state space model. The value of the melt index is obtained from the values of the manipulated and controlled variables generated from the control scheme. The control performance can be evaluated from the comparison between the computed melt index values and measured melt index values. The control scheme shows good tracking performance in the numerical simulations. We believe that the model developed in the present study can be effectively used to predict process variables as well as to control the melt index.     

鲁棒模型预测控制系统的评估基准

在控制系统的性能评估中,基准的设计是个重要问题。将基本设计极限理论推广到模型预测控制系统(MPC),建立性能评估基准。直接考虑多输入多输出系统的频域扰动,建立输出反馈鲁棒模型预测控制器。此控制器仅仅依赖于过程参数,也是令闭环系统达到控制性能极限的基准控制器。建立了用于评估的性能指标,提出基于此基准的性能评估程序,用以评价其他模型预测控制系统的性能。数学算例证实了这一评估程序的有效性。     

Performance monitoring of industrial controllers based on the predictability of controller behavior

This paper focuses on performance assessment of industrial controllers. Instead of using process or controller models, it is based on process data collected at regular time intervals. Data analysis includes a set of tests that are reviewed in the paper and implemented in a software system. A methodology based on the concept of the predictability of controller errors is also proposed for performance monitoring. It considers the time series of the error and verifies the existence of predictable patterns beyond the control horizon in each one of the controlled variables of the process. The result of the analysis is given as a performance index. Examples using industrial data from a refinery are provided.