Robust sliding mode‐based extremum‐seeking controller for reaction systems via uncertainty estimation approach

This paper deals with the design of a robust sliding mode‐based extremum‐seeking controller aimed at the online optimization of a class of uncertain reaction systems. The design methodology is based on an input–output linearizing method with variable‐structure feedback, such that the closed‐loop system converges to a neighborhood of the optimal set point with sliding mode motion. In contrast with previous extremum‐seeking control algorithms, the control scheme includes a dynamic modelling‐error estimator to compensate for unknown terms related with model uncertainties and unmeasured disturbances. The proposed online optimization scheme does not make use of a dither signal or a gradient‐based optimization algorithm. Practical stabilizability for the closed‐loop system around to the unknown optimal set point is analyzed. Numerical experiments for two nonlinear processes illustrate the effectiveness of the proposed robust control scheme. Copyright © 2017 John Wiley & Sons, Ltd.     

Self-optimising control for a class of continuous bioreactor via variable-structure feedback

A self-optimising controller is designed for stabilisation of a class of bioreactor exploiting sliding-mode techniques. The stability analysis for the class of bioreactor, in open-loop configuration, suggests that the optimal behaviour, respect to maximal biomass production, occurs in an unstable region (structurally unstable). In this contribution, a variable-structure controller is designed, exploiting the inhibitory effect of substrate concentration under the biomass growth rate, such that the closed-loop system reaches the optimal manifold where the effect induced by the growth rate gradient is compensated (favouring the maximum growth rate). The self-optimising comprises an uncertainty estimator which computes the unknown terms for increasing the robustness issues of the sliding-mode scheme. Numerical experiments illustrate the performance and execution of the control strategy considering different parameter values for biomass growth rate. The robustness and fragility of the proposed controller are also discussed with respect to the modelling uncertainty and small changes in the controller gains, respectively.     

UML辅助化工过程模拟软件设计

面向对象技术是目前获得广泛应用的软件设计方法，在化工过程模拟领域也有大量应用。UML(United Model Language，统一建模语言)采用图形方式和基于静态样式的软件设计方式进行软件开发，可有效地解决化工模拟软件开发过程中软件开发人员与化工专业人员交流困难的问题，并可提高软件的复用程度和开发效率，是一种有效的面向对象的辅助设计工具。文中利用UML建立了化工过程单元和化工过程系统的对象模型。实践分析表明，利用UML辅助化工过程模拟软件设计可有效降低软件分析设计的难度，提高软件设计的质量和速度。     

Optimal control of (bio-)chemical reactors: generic properties of time and space dependent optimization

This paper deals with the optimal control (OC) in the space domain of (bio-)chemical reactors. As an example, the determination of optimal heat exchanger temperature profiles of exothermic tubular reactors under the assumption of steady-state and plug flow characteristics is investigated. To enable a trade-off between process performance and energy loss a weighted cost criterion is defined. Application of the Minimum Principle of Pontryagin leads to extremal control profile structures which are very similar to those obtained during optimization (in the time domain) of well mixed bioreactors. The latter problem has been analyzed in detail over the last two decades. The analogy is reflected at various levels during analytical optimal control computations.     

On the robust design of sliding observers for linear systems

The restrictive character of well-known structural constraints, related to the matching conditions, for the sliding mode feedforward state reconstruction problem in linear, time-invariant, perturbed systems is critically reexamined from a new perspective. It is shown that, in generalized state space coordinates, a matched canonical state space realization exists which always allows discontinuous asymptotic stabilization of the observation error dynamics. The well-known structural conditions thus become largely irrelevant and robust asymptotic state estimation is shown to be feasible, for any perturbed observable system, by means of sliding mode observers.     

Real coded chemical reaction based optimization for short-term hydrothermal scheduling

This paper presents a real coded chemical reaction based (RCCRO) algorithm to solve the short-term hydrothermal scheduling (STHS) problem. Hydrothermal system is highly complex and related with every problem variables in a nonlinear way. The objective of the hydro thermal scheduling is to determine the optimal hourly schedule of power generation for different hydrothermal power system for certain intervals of time such that cost of power generation is minimum. Chemical reaction optimization mimics the interactions of molecules in term of chemical reaction to reach a low energy stable state. A real coded version of chemical reaction optimization, known as real-coded chemical reaction optimization (RCCRO) is considered here. To check the effectiveness of the RCCRO, 3 different test systems are considered and mathematical remodeling of the algorithm is done to make it suitable for solving short-term hydrothermal scheduling problem. Simulation results confirm that the proposed approach outperforms several other existing optimization techniques in terms quality of solution obtained and computational efficiency. Results also establish the robustness of the proposed methodology to solve STHS problems.     

非自衡化工生产过程的PID控制解析设计

针对非自衡化工过程难以控制及所得控制器参数调节无规律可循的问题,为提高过程控制品质,通过设计跟踪给定值控制回路和抑制干扰控制回路来实现非自衡化工过程的控制;利用最优控制理论、Taylor近似,设计得到的跟踪给定值控制器和抑制干扰控制器其PID参数可解析给出,每个控制器只有唯一的调节参数且两个回路的参数调节相互独立,最后定性分析了闭环控制系统的稳定性,仿真结果表明基于该控制系统可有效实现非自衡化工过程的控制。     

基于HLA架构下的化工安全虚拟现实仿真演练系统

介绍了运用高层体系结构(HLA)体系结构和虚拟现实技术对化工安全综合仿真平台的构建、系统实现的具体技术细节,以及HLA各联邦成员的设计方法。研制出的仿真系统能较好地模拟石化企业的生产状况、故障处理,以及在灾难性安全事故发生后联合消防和政府部门的协同演练。研究成果在石化企业得到了实际应用,取得较好的仿真效果,同时也可作为城市公共安全应急预案的仿真演练手段。     

基于EasyEnsemble的化工过程故障诊断性能改进

化工过程故障诊断中样本数据分布不均衡现象普遍存在.在使用不均衡样本作为训练集建立各类故障诊断分类器时,易出现分类器的识别率偏置于多数类样本的结果,由此产生虽正常状态易识别,但更受关注的故障状态却难以被诊断的现象.针对该问题,本文提出一种基于Easy Ensemble思想的主元分析–支持向量机(Easy Ensemble based principle component analysis–support vector machine,EEPS)故障诊断算法,通过欠采样方法抽取多数类样本子集组建多个新的均衡数据样本集,使用主元分析(principle component analysis,PCA)进行特征提取并使用支持向量机(support vector machine,SVM)算法进行训练,得到多个基于SVM的故障诊断分类器,然后使用Adaboost算法集成最终的分类,从而提高故障诊断准确性.所提方法被用于TE(Tenessee Eastman)化工过程,实验结果表明,EEPS算法能够有效提高分类器在不均衡数据集上的诊断性能和预报能力.     

Dissipativity-based observer and feedback control design for a class of chemical reactors

The problem of controlling a (possibly open-loop unstable) continuous exothermic reactor with non-monotonic kinetics, temperature measurements, reactant and heat exchange rates as manipulated inputs, and operation at maximum production rate is addressed within a robustness-oriented practical (input-to-state nonlocal) stability framework, according to the related detectability and relative degree structure. The result is a dynamical output-feedback (OF) controller made by the combination of a passive state-feedback (SF) nonlinear controller with a dissipative nonlinear observer. The proposed design methodology has: (i) solvability conditions with physical meaning, and (ii) a closed-loop stability criterion coupled with simple tuning guidelines. The proposed approach is tested with a representative case example through numerical simulations.     

基于改进神经网络的非线性系统观测器设计

根据非线性系统利用前馈网络的函数逼近能力,设计了一种神经网络观测器,并利用网络权值校正法,建立Lyapunov函数对观测器的稳定性进行了分析。为了加快训练速度,在训练网络时采用LM优化算法来实现,仿真结果不仅证明了所设计的神经网络观测器的有效性,还证实了神经网络改进算法后的优越性。     

Optimal adaptive control of (bio)chemical reactors: past, present and future

In this paper an overview of optimal adaptive control of (bio)chemical reactors is presented. Following the paradigm of the Minimum Principle of Pontryagin the derivation of optimal control sequences for fed-batch production processes is briefly revisited. Next, it is illustrated how the obtained optimal profiles can be exploited in the characterization of nearly optimal control sequences in terms of the qualitative behavior of the specific growth and production rates as function of the limiting substrates. Implementing this knowledge leads in a natural way to the design of (nearly) optimal adaptive feedback controllers. Special emphasis will lie on the potential of on-line biomass measurements (obtained with the Biomass Monitor) in the estimation algorithm of the growth kinetics being the adaptive component of the controller. Extensions towards fermentation processes with (i) multiple substrates and (ii) non-monotonic kinetics are also included. Finally, perspectives towards optimal adaptive control of not perfectly mixed (bio)chemical reactor systems, such as chemical tubular reactors, are outlined.     

基于模糊聚类神经网络的化工过程预报模型研究

本文提出了在化工过程预报中的模糊聚类神经网络模型,该模型具有提取典型数据、优化模糊规则及优化参数的优点,在化工过程预报实验中与传统方法相比预报结果的精度提高,计算时间缩短。     

On the global stability of conventional PID control for a class of chemical reactors

The stabilization properties of derivative control for chemical reactor stabilization have been rarely studied in the literature. In a pioneering work, Aris and coworkers (textitChem. Eng. Sci. 1959; 11 :199–206.) used linear analysis to show that derivative control offers greater stabilization flexibility than proportional control. The aim of this work is to show that mixed derivative and proportional control can yield global stabilization for a large class of continuously stirred tank reactors (CSTR) characterized by having stable isothermical dynamics. The stability proof exploits the structure of CSTR models where the nonlinearity is concentrated in the chemical reaction kinetics. It is shown that the proportional mode is a type of energy shaping to induce a unique equilibrium point, while the derivative mode can be interpreted as a global damping injection to reduce undesired transient effects, such as temperature overshooting and oscillations. A numerical example is used to illustrate the different features of mixed proportional and derivative control in chemical reactor dynamics. Copyright © 2011 John Wiley & Sons, Ltd.     

基于TE-DS的半监督化工过程故障诊断方法

针对现有基于深度学习的化工过程故障诊断方法通常需要完备的标签数据才能构建故障诊断模型等局限,提出一种基于时间集成—双重学生模型(temporal ensembling-dual student, TE-DS)的半监督化工过程故障诊断方法。该方法首先以双重学生模型为基础,通过分类项约束、稳定性约束和一致性约束条件指导相互训练,有效地缓解了误差累积情况的发生;然后利用时间集成(temporal ensembling)将多个先前网络评估的预测集成作为一致性正则化对象,达到缓解预测值噪声、降低模型训练时间的目的,以提高分类性能,实现故障诊断;最后通过田纳西—伊斯曼(Tennessee-Eastman)化工过程基准数据进行故障诊断实验,验证提出方法的有效性和可行性,并与BNLSTM、DCNN和MCLSTM等有监督方法进行比较,证明了TE-DS算法对故障诊断的优越性。     

基于关系数据库的化工过程模拟辅助设计专家系统的研究

根据专家系统基本原理,充分发挥关系数据库的强大数据处理能力,使用VISUAL BASIC6．0和MICROSOFT ACCESS 2003开发了一个用于化工过程模拟的专家系统。将知识和案例用数据库中表的形式表示出来,采用数据库语言进行推理,指导用户通过以往的相似案例来进行新工艺过程的模拟,从而使全流程模拟得到了简化。同时简洁友好的界面也便于领域专家操作。系统实现了与化工模拟软件ASPEN PLUS之间的接口,使二者可以进行数据传输。     

基于AutoCAD 2004的化工设计软件的开发与应用

在AutoCAD2004平台上开发了化工设计软件,阐述了软件开发的设计思想,制作和技术处理过程,在实际化工过程的设计中简化了设计中的繁杂步骤,提高了工作效率,在实践中有良好效果,该软件扩大了AutoCAD的应用范围,适用于现代教学与工程设计的需要。     

Fuzzy control of an exothermic chemical reaction using genetic algorithms

Establishing suitable control of complex chemical reactions, a requirement in a number of industries, poses a difficult problem because of nonlinearities and frequently changing process dynamics. Researchers at the U.S. Bureau of Mines have developed a technique for producing adaptive fuzzy logic controllers (FLCs) that are capable of effectively managing such complex chemical systems. In this technique, a genetic algorithm (GA) is used to alter the membership functions employed by a conventional FLC; an approach that is contrary to the tactic generally used to provide FLCs with adaptive capabilities in which the rule set is altered. GAs are search algorithms based on the mechanics of natural genetics that are able to rapidly locate near-optimum solutions to difficult problems. The Bureau-developed technique is used to produce an adaptive GA-FLC for a particular system in which an exothermic chemical reaction is conducted. Specifically, formaldehyde is reacted with ammonia in a continuous stirred tank reactor to produce hexamine and water. Results indicate that FLCs augmented with GAs offer a powerful alternative to conventional process-control techniques in the nonlinear, rapidly changing chemical systems commonly found in industry.     

基于规范变量分析的化工单元多变量统计监控

化工生产过程往往含有大量的过程变量,且过程多处于闭环控制作用下,产生的测量数据常常存在互相关和自相关。规范变量分析(CVA)通过最大化两个变量集间的相关度,实现对高维数据的降维,并得到一组最大限度地解释变量集中信息的规范变量,很好地解决了上述问题。本文介绍一种基于CVA的过程监控方法,并将此方法应用于一实际化工单元的过程监控,利用控制图,及时准确地检测到过程故障,表明了基于CVA的监控方法的有效性。     

一个基于知识库及自动推理机制的化学反应系统

提出了一种基于知识库及自动推理机制的化学反应系统,详细阐述了该自动推理系统的技术架构与算法实现.主要收集了无机化学知识,分析并提取相关化学反应规则,建立了相应的化学知识库,实现了由添加反应物到化学反应生成物的一系列自动推理过程.通过稀硫酸和铁反应实例表明,该系统对开发智能的虚拟实验平台,以及学生运用软件自主学习化学知识,掌握化学规律与现象,具有重要作用.