Experimental comparison and application of various parameter-adaptive control algorithms

Various recursive parameter estimation algorithms and controller design procedures can be combined to build up parameter-adaptive control algorithms. Two parameter estimation methods and six control algorithms have been selected, taking into account good convergence properties and small computational expense and regarding the conditions for closed-loop identification. The resulting 12 parameter-adaptive control algorithms are compared and tested with a process computer in on-line operation with analog simulated stable and unstable processes for stochastic disturbances and step changes of the reference signal. The results are very promising. In many cases a good control performance is achieved. As a priori knowledge only the sampling time, the process model order and time delay and in some cases a weighting factor for the process input signal are required. Some parameter-adaptive control algorithms with good properties are applied to digital adaptive control of an air heater. Conclusions are given for the selection of parameter-adaptive control algorithms, depending on the type of process and its disturbances.The adaptive control algorithms may be applied for adaptive control of constant and time variant, linear and weakly non-linear stable and unstable processes with process computers or micro computers or for self-tuning of control algorithms or tuning of conventional analog PID controllers, if external disturbances act on the loop.     

Computer control in the polymerization industry

Experiences in control of continuous and discontinuous polymerization processes did prove that process computers can successfully replace conventional control systems, yielding a better performance. It has also been shown that marked process improvements are possible by application of advanced control concepts such as multivariable control, adaptive control and dynamic optimization. Because of the complexity and size of new batch systems, computer control is widely accepted. Its ability to enforce on-off sequencing and continuous control on the batch process and its adaptation flexibility to all process needs ensures high production levels by minimizing labor cost and lost production on idle equipment.     

Implementation of on-line control in chemical process plants

A range of identification, estimation and control algorithms has been implemented and tested on a chemical process plant/process control computer system which is typical of installations in the process industries. The plants studied are a gas-separating unit consisting of a pair of 9 m high absorption/distillation columns and a two-stage fractional crystallization plant. All on-line estimation and control was performed by a Honeywell 516 computer system. The topics studied on the plants included continuous on-line estimation of states and chemical process parameters using Kalman filtering techniques, the use of these estimates in various control algorithms, the application of optimal control theory to a variety of problems (minimum variance control, adaptive control, time optimal control), and the identification of process models for subsequent use in the design and implementation of multivariable control algorithms. In all cases, the implementation of these aspects of modern control theory on a real process plant was successful, but pointed to several non-trivial complications which must be resolved before these algorithms can be adopted for general use in the process industries.     

Simulations of adaptive controllers for a paper machine headbox

The paper headbox is a crucial part of a paper machine, largely influencing the paper quality. Since this can be improved by better control, the evaluation of advanced control methods is certainly justified from an economical point of view. Not only do disturbances have to be rejected, but smooth startups and fast setpoint changes must also be possible. To design a good controller, some parameters need to be known, the determination of which can be cumbersome. However, this can be considerably alleviated by adding an on-line parameter estimator to the controller. This allows the controller to adapt itself to slowly changing process characteristics. In this paper different adaptive control methods are used on the simulated process and compared to the classical PI-controls. Particularly, a single-output self-tuning controller with feedforward action and a multivariable adaptive deadbeat controller are promising. The last one provides simultaneous offset-free control of both process outputs.     

Advanced control and on-line process optimization in multilayer structures

The paper demonstrates the place, role and mutual interaction of advanced control algorithms and on-line set-point optimization in process control structures. First, a multilayer control structure resulting from a functional decomposition is briefly presented. The role and selected realizations of advanced control algorithms, in particular mostly applied now model predictive control (MPC) ones, at direct control and supervisory constraint control layers is discussed. Then possible solutions to on-line set-point optimization, depending of disturbance dynamics, are presented: dynamic set-point optimization including involved structures based on temporal decomposition, and steady-state set-point optimization for cases with disturbance dynamics both much slower than and comparable with the process dynamics. For the last case, important in industrial practice, different structures of interaction and even integration of MPC and steady-state optimization are discussed. The topics are illustrated by briefly presented examples, selected from given references.     

基于模糊遗传算法的选矿破碎系统优化控制

矿石破碎是选矿工业流程中的关键环节,破碎过程要求机腔料位稳定,以提高破碎处理流程的工作效率.针对给料机及破碎机具有的惯性、滞后、非线性时变特点,提出了一种基于模糊遗传优化算法的碎矿系统给矿量优化控制策略,控制器采用模糊自适应PID控制算法,并利用遗传算法对控制器参数进行优化,以提高参数在线寻优能力.仿真结果验证了本文提出的优化控制策略的有效性,表明控制系统具有较好的动态品质和较强的抑制干扰能力.     

Energy management technology in pulp,paper, and allied industries

This paper reviews the state of the art and trends in paper and allied industry energy management. As a structural approach, the plant is first partitioned into unit operations convenient for the definition of multilevel control and optimization schemes: The applicable methods of control and system theory useful for energy management are presented. Problems and solutions at each level are identified and discussed. The process of implementation of energy management functions with computers is included along with a summary list of major energy mangement functions. Furthermore, some important optimization examples are presented and several methods are discussed. Although the paper emphasizes power generation and energy recovery area, the research on total mill energy management is reviewed and the main results are briefly presented.     

On-line identification of a heat exchanger with a process computer—A case study

For on-line identification and parameter estimation of industrial processes with process computers an identification program package was developed. Three appropriate identification methods can be selected: recursive least squares, recursive instrumental variables and recursive correlation analysis with least squares. The program package also includes: signal generation, determination of model order and time delay, data filtering for the elimination of low frequent disturbances, model verification and plotting of intermediate and final results. Practical results and comparisons with the identification package are shown for an industrial size steam-heated heat exchanger.     

PLC控制系统中基于OPC技术的多上位机解决方案

在PLC控制系统中,常常需要多个监控上位机而控制系统通信方式只允许单上位机,这时可以通过建立客户机与服务器结构来实现多机监控.利用和上位机组态软件相关的OPC技术就能简单实现多机监控配置,其实现的方法有两种,一种是利用组态软件本身集成的OPC驱动来建立客户端访问连接,另一种是用高级语言开发基于OPC技术的客户端访问程序.通过工程及实验,证明这两种技术都很好的满足多上位机监控需求.     

HIERARCHICAL DYNAMIC OPTIMIZATION FOR LINEAR DISCRETE SYSTEMS

In this paper an on-line multilevel suboptimal control procedure is developed for large-scale, time-invariant, and discrete linear systems with quadratic performance criterion, and measurement disturbances having arbitrary statistical distributions. The on-line coordination procedure as reported here employs an upper-level intervention through interaction estimates and goal modifications in order to modify lower-level subsystem optimization problems. Their individual controls are applied to the system and the resulting output is estimated by Kalman Type filter and performance information is fedback to the upper level unit. A reference control approach is used to up-date intervention variables over a sequence of time instants to improve on the control being applied to the process. In the computer simulation of the process, it was found that the actual overall cost for systems using this on-line multilevel control procedure is within ±10% of the cost resulting from a conventional overall optimal control policy.     

乙烯氧氯化反应过程微机辅助监测优化的实现

工业氯乙烯生产装置是一类大规模存在的化工工业装置，本文针对其中乙烯氧氯化法反应过程特点设计的微机辅助监测优化系统，对该过程的运行特征进行在线监测，并进行数据处理和工艺分析，为该过程的优化提供了依据，此外，对这一类的化工工业装置微机辅助监测优化系统设计进行探讨，为如何在工业装置优化领域利用计算机这一先进工具提供了一个范例，并就此提出了具有普遍意义的功能模型和运行逻辑，以供类似的系统开发借鉴。     

水泵性能计算机数据采集系统程序设计

介绍了水泵性能计算机数据采集系统硬件、软件设计的基本原理,以及用MATLAB完成程序设计的方法。结果 表明:系统运行良好,数据采集与处理结果可靠;利用计算机采集泵性能数据,自动绘制泵的性能曲线,可以提高数 据采集精度和效率,显著降低劳动强度。用MATLAB编程能很好地解决端口访问、用户界面、数据处理、图像表征等 问题。     

Explicit output-feedback nonlinear predictive control based on black-box models

Nonlinear model predictive control (NMPC) algorithms are based on various nonlinear models. A number of on-line optimization approaches for output-feedback NMPC based on various black-box models can be found in the literature. However, NMPC involving on-line optimization is computationally very demanding. On the other hand, an explicit solution to the NMPC problem would allow efficient on-line computations as well as verifiability of the implementation. This paper applies an approximate multi-parametric nonlinear programming approach to explicitly solve output-feedback NMPC problems for constrained nonlinear systems described by black-box models. In particular, neural network models are used and the optimal regulation problem is considered. A dual-mode control strategy is employed in order to achieve an offset-free closed-loop response in the presence of bounded disturbances and/or model errors. The approach is applied to design an explicit NMPC for regulation of a pH maintaining system. The verification of the NMPC controller performance is based on simulation experiments.     

A modern approach to industrial process control

The history of industrial process computer control now spans over 10 years. During this time control theory has transgressed from the frequency domain to the time domain, and yet few applications of these modern methods to industrial processes can be found in the literature. This paper attempts to temper the current state of computer process control with some historical perspective and then goes on to describe an application of modern control techniques to the basic oxygen steel-making process. This application of adaptive filtering and nonlinear state estimation is used to illustrate that modern methods can be used to compensate for a lack of process knowledge. The point of emphasis is that these modern methods can replace the extensive modeling and simulation phases which historically have retarded the success of many on-line computer control projects. The paper is intended to stimulate more applications of modern control methods to industrial processes.     

城市道路交叉口计算机辅助设计系统

为提高平面交叉路口的通行能力,基于中国城市道路交通设计理论与方法,运用软件工程的思想完成城市道路交叉口计算机辅助设计系统的设计与实现.系统的数据结构设计合理,能为未来交通控制方案的生成和仿真评价软件的开发提供接口.应用实例表明该系统内核模型符合我国道路交通的实际情况,能大大提高道路平面交叉口设计的效率.     

Adaptive Synchronization Control of the Magnetically Suspended Rotor System

An adaptive controlapproach to the implementation of synchronization control forthe magnetically suspended rotor system is presented. The controlsystem enables a translatory mode for the whirling rotor alongthe bearing axes, thereby eliminating the gyroscopic effectsthat can vastly degrade the rotor stability at high speeds. Thecontrol method features the integration of adaptive control andcross feedback control for the electromagnetic circuit, in whichan adjustment system is trained to tune the adaptation parametersto minimize the differential errors of state variables throughouta cross coupling controller. Under this control process, thecontrol variables are updated in a way to suppress the conicalmodes against the gyroscopic forces. This paper develops twokinds of synchronization control algorithms in conjunction withan optimization design, and the simulation of synchronizationcontrol for a magnetically suspended rotor system is presented.     

智能材料和智能结构(3)——智能结构的设计、控制和探测

智能结构是当代最具挑战性、最活跃的新研究领域之一。智能结构技术包括材料设计、高等执行和传感技术、自适应计算机算法和能量利用最佳化。智能结构的应用范围从空间飞行器和飞机到大型民用建筑和桥梁。本文综述了智能自适应光学系统波前传感器的设计、智能mm波望远镜的表面控制和振动抑制、智能建筑物层间漂移的激光叉丝监测、智能圆柱形结构应变的光纤光栅测量系统和智能结构的长周期光栅传感器。     

Optimal genetic manipulations in batch bioreactor control

Advances in metabolic engineering have enabled bioprocess optimization at the genetic level. Large-scale systematic models are now available at a genome level for many biological processes. There is, thus, a motivation to develop advanced control algorithms, using these complex models, to identify optimal performance strategies both at the genetic and bioreactor level. In the present paper, the bilevel optimization framework previously developed by the authors is coupled with control algorithms to determine the genetic manipulation strategies in practical bioprocess applications. The bilevel optimization includes a linear programming problem in the inner level and a nonlinear optimization problem in the outer level. Both gradient-based and stochastic methods are used to solve the nonlinear optimization problem. Ethanol production in an anaerobic batch fermentation of Escherichia coli is considered in case studies that demonstrate optimization of ethanol production, batch time, and multi-batch scheduling.     

乳腺X线图像计算机辅助诊断技术综述

近年来,乳腺癌严重威胁全球女性的身体健康,乳腺X线摄影是乳腺癌筛查的有效影像检查手段.乳腺X线图像计算机辅助诊断(computer aided diagnosis,CAD)运用计算机视觉、图像处理、机器学习等人工智能先进技术,自动分析处理乳腺X线图像,可为医生在临床中提供重要的诊断参考.主要面向肿块和微钙化病变检测、分...     

ProOpter: An advanced platform for production analysis and optimization

This paper presents the prototype of an advanced platform for production analysis and optimization, referred to as ProOpter. The platform was developed to support the recently derived concept of holistic production control (HPC), which relies on model-based control. The prototype is comprised of a set of off-line and on-line modules. The off-line modules support the definition of key performance indicators (KPIs), the selection of the most influential input (manipulative) variables, and the identification of a simple production model from historical data. The on-line modules enable KPI prediction and suggest actions to the production manager, employing model-based production control and/or optimization techniques. In this way, a new decision-support reasoning based on historical production data can be introduced. ProOpter has a modular design and can be used as an add-on to existing production IT systems since it relies on established industrial communication standards. The use of the platform is validated on the well-known Tennessee Eastman benchmark simulation process and on two industrial case studies.