Control of the quality of polymer products in continuous reactors: comparison of performance of state estimators with and without updating of parameters

In the paper the control of the product quality in polymerization reactors is analysed in the presence of persistent perturbations (unmodeled disturbances, modeling errors), as met in industrial reactors. The free radical polymerization of methyl-methacrylate in a continuous stirred tank reactor is studied. It is shown that state estimators (Extended Kalman Filters) with constant parameters cannot give offset free performance. Criteria for the selection of a set of parameters to be updated as additional states in the filter and to evaluate their effectiveness in opposing the action of realistic perturbations are given by an analysis of the linearized model of the system. Performance of different types of estimators, including one and two-time scale filters, with and without updating of parameters, is analysed by simulation on the full order process and the predictions made by previous analysis are confirmed. In the most common case of presence of perturbations affecting the energy balance and the concentration of initiator in the reactor, offset free control of the molecular weight of the product can be achieved by means of a filter which is based only on measurements of temperature and conversion and makes an update of two parameters. In the case that also the kinetic model of the polymerization reaction is affected by errors, a two-time scale filter, which makes use also of Molecular Weight values and updates three parameters, becomes necessary to obtain offset free performance.     

Neural Network Feedback Control: Work at UTA’s Automation and Robotics Research Institute

This is an outline of research in neural networks for feedback control done since the mid 1990s at the Automation and Robotics Research Institute (ARRI) of The University of Texas at Arlington (UTA). It shows how the developments of Intelligent Control Systems based on neural networks have followed three main generations. This statement provides a short, broad-brush perspective on the development of intelligent neural feedback controllers.     

化工企业环境因素的评价

化工企业环境因素评价是建立环境管理体系的核心任务，化工企业生产过程的特点决定了其环境因素数量多、环境影响大、识别评价难、控制难度大。本文介绍了化工企业环境因素评价的技术方法和过程，可以为提高环境因素评价的科学性、客观性和充分性提供参考。     

煤矿矿井水检测质量控制措施探讨

探讨了影响煤矿矿井水检测质量的主要因素,按照全过程、全要素控制的理念提出了检测前、检测中和检测后的控制措施。     

乌江渡水电站扩建工程开挖爆破对原水电站建筑物震动影响的控制研究

为确保原有的乌江渡水电站水工建筑物和发电设备以及扩建工程建筑物的施工安全,加快扩建工程施工进度,本扩建工程施工中对关键部位开挖所产生的爆破震动影响实施全面而有效的实时爆破监控,并根据监控成果的研究指导开挖爆破作业,以确定符合实际的安全爆破震动参数。     

肝单光子发射计算机断层若干物理因素的讨论

我们于1985年对我院1984年开展肝单光子发射计算机断层以来的52例肝病人进行了分析总结。结果表明,肝单光子发射断层在诊断肝内占位性病变方面比普通肝静态γ照相有许多优点。需要指出的是,肝单光予发射断层的若干优点及诊断的准确性是与物理条件的正确选择和应用密切相关的。本文根据至今积累的近100例断层经验,从技术方面介绍了影响单     

低碳微合金钢中的晶内铁素体及组织控制

回顾和评述了晶内铁素体的发现、发展及其与组织控制的关系.介绍了晶内铁素体的形核机制和影响晶内铁素体形成的因素,讨论了晶内铁素体的三维形态和长大动力学,并从以上几方面分析了晶内铁素体对低碳微合金钢组织细化的重要作用和影响.     

Optimal predictor for a singular random process

An optimal predictor is developed for a singular random process generated by a known system driven by a white noise sequence. The properties of the predictor are compared with those of the optimal predictor for a nonsingular random process.     

A stochastic maximum principle for systems with jumps, with applications to finance

We consider a stochastic control problem with linear dynamics with jumps, convex cost criterion, and convex state constraint, in which the control enters the drift, the diffusion, and the jump coefficients. We allow these coefficients to be random, and do not impose any L^p-bounds on the control.

We obtain a stochastic maximum principle for this model that provides both necessary and sufficient conditions of optimality. This is the first version of the stochastic maximum principle that covers the consumption–investment problem in which there are jumps in the price system.     

Lyapunov‐stable discrete‐time model reference adaptive control

Discrete‐time model reference adaptive control (MRAC) is considered with both least squares and projection algorithm parameter identification. For both cases complete Lyapunov proofs are given for stability and convergence. The results extend the approach of Johansson (Int. J. Control 1989; 50 (3):859–869) to include Lyapunov stability for MRAC when the normalized projection algorithm is used for parameter identification. Copyright © 2005 John Wiley & Sons, Ltd.