多智能体协调技术在热连轧中的应用

本文以典型的流程工业过程为对象,结合分布式工业过程控制的特点,分析了多智能体应用于复杂工业过程控制的可行性、必要性;提出了一种基于工业过程控制的多智能体系统的体系结构及其协调控制过程.板带热连轧机过程控制是典型的分布式过程控制对象,文章从综合控制的角度出发提出热连轧机工业生产过程多智能体系统的体系结构,给出了体系结构中各功能模块的组成及其处理过程,并重点分析了加热炉控制的协调过程.     

基于Internet远程实验系统模糊控制算法的实现

描述了基于Internet远程过程控制实验系统以及模糊控制算法在此控制系统中的实现。实验人员可以利用连接在In-ternet网上的任意一台计算机远程操作实验装置,可远程选择模糊控制算法,进行远程过程控制实验。测试结果表明使用模糊控制算法应用于此远程过程控制实验系统中,系统响应快、超调小、具有较高的控制精度,满足过程控制实验的要求。     

霍尼韦尔任命NORMAN GILSDORF为过程控制部新任总裁

2009年1月9日,霍尼韦尔（NYSE：HON）宣布任命Norman Gilsdorf为其过程控制部新任总裁（以下简称Norm）。Gilsdorf此前任霍尼韦尔过程控制部全球副总裁,欧洲、中东以及非洲区总经理。原霍尼韦尔过程控制部总裁Jack Bolick先生光荣退休,Jack Bolick先生在过去10年中一直供职于霍尼韦尔,其中6年担任霍尼韦尔过程控制部总裁职务。     

霍尼韦尔任命NORMAN GILSDORF为过程控制部新任总裁

2009年1月9日,霍尼韦尔（NYSE：HON）宣布任命Norman Gilsdorf为其过程控制部新任总裁（以下简称Norm）。Gilsdorf此前任霍尼韦尔过程控制部全球副总裁,欧洲、中东以及非洲区总经理。原霍尼韦尔过程控制部总裁JackBolick先生光荣退休,JackBolick先生在过去10年中一直供职于霍尼韦尔,其中6年担任霍尼韦尔过程控制部总裁职务。     

关于石油化工计算机过程控制的几点看法

本文结合当前石油化工过程控制中计算机应用情况,提出计算机过程控制开发重点为静态优化闭环控制系统,工艺是过程控制的主体,工艺过程数学模型开发则是关键,精馏系统是开发的突破点.系统开发和推广应用都要有设计参加.     

微机在化工生产过程控制中应用现状及今后对策

随着计算机技术的发展,微机在我国化工生产过程控制中得到了应用。文中列举了微机在化工生产过程控制中众多应用实例,并作了分析比较,对今后的发展提出了建议。     

一种热轧过程计算机系统集成中间件平台

随着过程控制系统逐渐从封闭式系统向开放式系统转变,中间件技术在过程控制系统集成开发中的作用越来越大。本文针对热轧过程控制计算机系统集成开发中所存在的问题,提出了一种热轧过程控制计算机系统集成中间件平台的开发方案,该中间件平台具有实时进程调度管理、可扩展的通讯管理、实时数据管理、MVC架构下的实时画面管理、报表生成等功能,并已在某钢厂的二热轧系统改造中成功应用。     

工业过程控制传感器

概要介绍了在工业过程领域中应用的传感器 ,论述了过程控制传感器的发展现状和需求、并对过程控制传感器技术和市场及发展趋势进行了预测     

PKS+TRICON+PLC结构在神华煤制油过程控制中的应用

PKS+TRICON+PLC结构是神华煤制油过程控制中的主导控制结构。对控制系统组态中如何完善软、硬件的组态,提高煤制油过程控制应用水平进行探讨。     

基于Internet远程实验系统神经网络控制算法的实现

描述了基于Internet远程过程控制实验系统以及基于BP神经网络整定PID控制算法在此控制系统中的实现。实验者可远程操作实验装置,可远程选择控制算法。测试结果表明应用基于BP神经网络整定PID控制算法于此远程过程控制实验系统中,系统动态响应快、具有较高的控制精度,满足过程控制实验的要求。     

A multiregion fuzzy logic controller for nonlinear process control

Although a fuzzy logic controller is generally nonlinear, a PI-type fuzzy controller that uses only control error and change in control error is not able to detect the process nonlinearity and make a control move accordingly. In this paper, a multiregion fuzzy logic controller is proposed for nonlinear process control. Based on prior knowledge, the process to be controlled is divided into fuzzy regions such as high-gain, low-gain, large-time-constant, and small-time-constant. Then a fuzzy controller is designed based on the regional information. Using an auxiliary process variable to detect the process operating regions, the resulting multiregion fuzzy logic controller can give satisfactory performance in all regions. Rule combination and controller tuning are discussed. Application of the controller to pH control is demonstrated     

A digital quality control system for an industrial dry process rotary cement kiln

A multivariate autoregressive moving average (ARMA) model for an industrial dry process rotary cement kiln is identified, from real process data, using the maximum likelihood method. The model obtained is then used in computing a controller for quality control of clinker production. It is shown that it is relevant to compute a minimum variance controller subject to restrictions both in the controller structure and the variances of the control signals. The resulting controller is finally implemented on the cement kiln process, together with a target adaptive controller for automatic adjustment of the clinker quality setpoint, in order to save energy.     

An alternative structure for next generation regulatory controllers. Part II: Stability analysis,tuning rules and experimental validation

We recently developed, as an alternative to the PID controller, a novel 4-mode control scheme that takes full advantage of modern electronic hardware components, and whose tuning parameters are directly related to controller performance attributes (robustness, set-point tracking, and disturbance rejection); its achievable performance is better than that of the PID controller, and it can be designed and implemented much more directly and transparently. In this companion paper we present robust stability results for the proposed controller, for any given plant/model mismatch; these results are then used to generate simple tuning rules for the controller. The effect of noise on controller performance is explicitly considered and modified tuning rules are proposed for excessively noisy processes. The controller tuning results and procedure are then illustrated via experimental testing and validation. First, water level control in a simple laboratory scale process is used to illustrate the design, tuning, and implementation of the RTDA controller. We use this process primarily to evaluate the controller performance and illustrate how the tuning parameters influence, directly and independently, the controller performance attributes. The controller is then implemented on a pilot-scale physical vapor deposition process to demonstrate its performance on a more complicated process that is prototypical of 21st century manufacturing. We demonstrate that the proposed controller achieves improved performance with minimal tuning effort.     

烘丝过程中的组合积分控制器与双重控制研究

在烟草行业的烘丝过程中,烟丝的出口水分作为被控对象常常具有大滞后与强非线性的特性,且在工艺流程中通常存在干扰因素;当前,这一过程中大多仍采用传统PID控制器,存在响应稳态误差大、响应时间长等问题,进而影响烟丝的最终品质;针对这一情况,引入组合积分控制器替代传统PID控制器在烘丝过程中的作用;同时引入双重控制,并与组合积分控制器相结合;针对控制对象进行的仿真实验结果表明,这一新型控制策略在烘丝过程出口水分的控制效果上明显优于传统PID控制器,稳态误差较小且响应迅速,证明了组合积分控制器运用在双重控制系统中时具有优异的动态性能与鲁棒性;最后,这一新型双重控制算法已成功应用到烟草行业烘丝过程的水分控制上。     

基于NT降阶的乘积型区间二型模糊控制器结构分析

目前区间二型模糊控制器的结构分析主要基于Zadeh的取小推理和KM降阶算法。KM算法是一循环迭代过程,没有解析解,无法进行控制器的稳定性分析,且取小推理需要进行输入空间的划分,过程较为繁琐。提出了一种简化的区间二型模糊控制器分析方法,该方法首先采用乘积推理,模糊规则的激发隶属度为输入变量隶属度的乘积,统一了控制器的表达式形式,避免了输入空间的划分过程,模糊控制器的结构分析更加简单。二型模糊集合采用NT降阶算法,该算法直接利用首隶属度函数的上、下限的平均值来进行解模糊化操作,避免了迭代计算,简化了降阶过程。控制器的表达式等效于一个增量式PI（位置式PD）控制器,其比例增益、积分增益以及补偿项均为非线性可调。而且还能得到控制器的闭环表达式,易于进行区间二型模糊控制器的稳定性分析与设计等。     

Performance assessment of single-loop industrial controllers

The most common metric for controller performance assessment is a comparison of the process output variance to that which would have been obtained if some optimal controller had been applied to the process over the same time frame. Usually this optimal controller is a minimum variance controller, as a metric based on this controller requires a minimum of process knowledge and no plant tests. While minimum variance controllers by definition contain an accurate disturbance model, industrial controllers contain a simple fixed disturbance model, which may or may not be an accurate representation of the actual disturbance. Shown in this paper is the effect that this simple disturbance model has on performance indices, and methodologies for controller performance assessment that accounts for this simple model. In addition, a performance metric for non-deadtime-compensated (i.e., PID) controllers is shown.     

MFA控制器控制大时滞过程的实验研究

以大时滞过程为研究对象,对无模型自适应(MFA,M0del-freeAdaptive)控制器进行了仿真和实验研究,并与传统的PID控制器进行了比较,同时进行了鲁棒稳定性的研究。实验结果表明,无模型自适应控制器具有良好的输出跟踪性能,有很强的自适应能力和鲁棒性,能有效地控制复杂过程,特别在控制大时滞过程方面与传统的PID控制器相比,有着明显的优越性。     

Variable-structure PID controller for level process

A variable-structure (VS) PID controller for the level process is proposed. A methodology of analysis of its stability and performance is given. It is proposed that stability of the VS system can be approximately analyzed via the describing function method. The describing function of the VS PID controller is derived. It is shown that the system with the VS PID controller is quasi-linear. Tuning rules for the VS PI controller for the level process are given. It is shown via the theory and simulations presented that, if properly tuned, the VS PI controller has higher performance than the conventional PI controller for the process considered.     

Improved PI controller based on predictive functional control for liquid level regulation in a coke fractionation tower

Due to limitations of hardware, cost and so on, the application of proportional-integral-derivative (PID) control is more convenient than predictive control. However, predictive control usually has better performance than traditional PID control, thus it is important to combine the advantages of these two control algorithms. A novel PI controller optimized by predictive functional control (PFC) is proposed and tested on liquid level in the industrial coke fractionation tower in this paper. Since this kind of process always shows the integrating behavior, a P controller is first used for it to generate a self-balancing generalized process, then the PFC based PI control is designed for the generalized process. The resulting controller displays the performance of both PFC and PI control with easy implementation in practice. The performance of the proposed PI controller is compared with traditional PI controller in terms of regulatory/servo set-point tracking, disturbance rejection and measurement noise issues, from which results show that the proposed PI controller provides better performance than traditional PI controller.     

Application of discrete-time quantized data controllers to systems with disturbances

In a recent paper, a new method for the digital control of a continuous-time system based on a table look-up technique was presented. This digital controller is called a discrete-time quantized data (DTQD) controller. In order to minimize the number of table entries, a grid embedding process is proposed. This control technique proved successful when applied to the regulator problem. However, when a DTQD controller using the grid embedding process is applied to a continuous-time system with additive disturbances, the performance of the DTQD controller degraded, causing oscillations and possible limit cycle phenomena. In this paper, the grid embedding process is replaced with a continuous scaling process. The continuous scaling process retains the advantages of the grid embedding process in reducing the number of table entries. In addition, it reduces the amount of oscillation in the system response when disturbances are present.