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.     

Application of multi-level control of calenders in the tire industry

The interest in integrated computerized process control systems has recently increased due to demonstrated economic returns. The extension into new industries required the development of new sensors and solution of new control problems. This paper examines the potential candidates for process control in the tire manufacturing industry with emphasis on multi-level computer control application to the calendering process. The measurement techniques are discussed. Various control functions as part of this multi-level system are also described. The interactive behavior of the calender requires the design of a multi-variable control algorithm. The derivation of the algorithm, simulations and field results are also presented.     

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.     

Plant-wide hierarchical optimization and control of an industrial hydrocracking process

Hydrocracking is a crucial refinery process in which heavy hydrocarbons are converted to more valuable, low-molecular weight products. Hydrocracking plants operate with large throughputs and varying feedstocks. In addition the product specifications change due to varying economic and market conditions. In such a dynamic operating environment, the potential gains of real-time optimization (RTO) and control are quite high. At the same time, real-time optimization of hydrocracking plants is a challenging task. A complex network of reactions, which are difficult to characterize, takes place in the hydrocracker. The reactor effluent affects the operation of the fractionator downstream and the properties of the final products. In this paper, a lumped first-principles reactor model and an empirical fractionation model are used to predict the product distribution and properties on-line. Both models have been built and validated using industrial data. A cascaded model predictive control (MPC) structure is developed in order to operate both the reactor and fractionation column at maximum profit. In this cascade structure, reactor and fractionation units are controlled by local decentralized MPC controllers whose set-points are manipulated by a supervisory MPC controller. The coordinating action of the supervisory MPC controller accomplishes the transition between different optimum operating conditions and helps to reject disturbances without violating any constraints. Simulations illustrate the applicability of the proposed method on the industrial process.     

Goal and predictive coordination in two level hierarchical systems

The multilevel system theory applies two general methods of coordination, which influences the manner of subsystem management—goal and predictive coordinations. Both these general types of coordination perform multiple data transfer between the hierarchical levels and delay the evaluation and implementation of a global optimal solution of a control problem. The paper demonstrates a coordination policy, which decreases the information transfer in the hierarchical system, titled “noniterative” coordination. The last is developed both for goal and predictive coordination strategies. The mathematical foundations of these two noniterative coordination strategies are presented. Comparative analysis is performed to identify peculiarities and drawbacks for the real time management of two level hierarchical systems. Assessment of the computational workload and speed of the coordination, expressed as “flops” numbers is done for the case of nonlinear optimization problems. Both the noniterative coordination strategies benefit the real time operation in the multilevel system by reducing the iterative computations and the data transfer between the hierarchical levels. The predictive coordination has potential in speeding the management process and resource allocation, due to the decomposition approach, which is applied.     

Pulp,paper and allied industry digital process control systems status and trends

Digital process control applications in the paper industry are now some 17 yr old. During this development, the Process Control Committee of the Technical Association of the Pulp and Paper Industry has been active in educational programs, defining standards, determining economics and measuring the extent, character, and impact of these systems. Several surveys have been conducted to support these activities. The results of these surveys are summarized in this paper. To provide a more current data base for presentation to the IFAC PRP₃ Conference in Brussels, Belgium, May 24–26, 1976, one of these surveys was updated in February 1976.     

Management and control systems in the steel industry

Kimitsu Works, built during the period of Japan's rapid economic growth, was conceived and designed as a modern plant with emphasis on applying computers throughout its operation.Since the prototype of Kimitsu Integrated Information System (KIIS) was completed in 1970, KIIS has realized an integration of systems for processing information and data on steel plant operations from the receiving of orders to the shipping of products by assigning various functions of production control and operating control to a hierarchical structure of business computers, and process computers.After the oil crises, however, restructuring and modification of the existing systems became necessary to adopt to changes in the economy and plant-operating conditions, and to meet changes in manufacturing processes. Against such background, computer applications have been further expanded to fit the application of online systems to administrative areas in addition to the area of production control, and new computer systems have been developed to facilitate the control and analysis by staff departments.     

A holistic control philosophy for the process industries

The objective of this paper is to give a holistic picture of the economic control as part of the management function in the process production organizations. The systematics described is a three dimensional life cycle model of the systems development. The first dimension defines the levels of decision making in the organization. The second dimension describes the various functions of the production organization and the third dimension formulates different abstraction models of the system in question.     

Decomposition methods in multiobjective discrete-time dynamic problems

Decomposition methods for multicriteria dynamic (discrete-time) problems are derived. In these methods, the original problem is reduced to a series of multicriteria subproblems related to individual stages. Hence, the dimensionality of decision variables in each subproblem is smaller than in the original problem. The following decomposition procedures for such problems are developed: (1) a dynamic programming method, (2) a two-point boundary value problem method, (3) multilevel methods, and (4) the formulation of a temporal hierarchy. For completeness, methods for multicriteria dynamic problems are reviewed that, at the outset, transform a problem into a series of single-objective problems. Formulation of the multiobjective problem in the context of a multilayer temporal hierarchy is also presented. The temporal structure motivates problem simplification by decomposing the overall decision-making problem according to relative time scales.     

Multilevel optimization algorithms in computer aided production control in process industry

The use of optimization techniques in production control is discussed. Two optimization problems in relation to typical process industry complexes are formulated. A modified version of Tamura's algorithm is reviewed. The promising performance of the computerised algorithms is illustrated by numerical results. DISPATCHER, a practical operative decision support system, is described.     

最优控制在过程工业中的应用与展望

最优控制理论在过程工业中应用的越来越广泛,过程工业包括石油化工、电力、冶金化工等诸多行业,他们在我国国民经济中起着举足轻重的作用。随着最优控制理论重要性不断增强,本文综合性的阐述了关于最优控制的基本原理,最优控制的实现过程是通过建立受控系统的动态方程,在容许控制以及选定目标集范围内达到性能指标的最大或最小。本文还阐述了它所用于研究的主要过程控制问题、最优控制问题的主要解决方法,以及近几年最优控制在过程控制方面的最新进展和发展前景。     

产品质量与生产过程的集成控制: 双率采样数据方法

本文在集成控制的框架下研究了工业过程中产品质量和生产过程的实时一体控制问题.首先,基于双速率采样数据提出了产品质量和生产过程的集成控制方案.然后,把控制器设计问题归结为求解一组非线性矩阵不定式,进而提出基于同伦算法的控制器设计方法.最后,通过数值仿真说明所提方法的有效.     

A neurofuzzy scheme to on-line identification in an adaptive–predictive control

A neurofuzzy scheme has been designed to carry out on-line identification, with the aim of being used in an adaptive–predictive dynamic matrix control (DMC) of unconstrained nonlinear systems represented by a transfer function with varying parameters. This scheme supplies to the DMC controller the linear model and the nonlinear output predictions at each sample instant, and is composed of two blocks. The first one makes use of a fuzzy partition of the external variable universe of discourse, which smoothly commutes between several linear models. In the second block, a recurrent linear neuron with interpretable weights performs the identification of the models by means of supervised learning. The resulting identifier has several main advantages: interpretability, learning speed, and robustness against catastrophic forgetting. The proposed controller has been tested both on simulation and on a real laboratory plant, showing a good performance.     

Current status and future trends of CIM in the Japanese steel industry

The growth of the Japanese steel industry has been supported by three factors: operation, equipment, and management technology. Computer-integrated manufacturing (CIM) is the core of management technology. CIM's purpose is to improve production efficiency through computer integration of data covering the staff (design and production control) and management department as well as the production line process department (order entry, manufacturing, and shipment). In this paper, an overview of the Japanese steel industry's system development process is given and the steps taken in order to establish the CIM system are described. The organization, operation, and improvement of operational capability, along with marketing and production-related systems, are integrated. Furthermore, an integrated system model is given as a CIM conceptual model. In closing, reference is also made to the challenges facing CIM in the Japanese steel industry as well as future directions to be taken.     

过程控制研究的一些进展

随着新材料、新工艺的不断涌现,对反馈控制系统性能的要求更加严格和精确,在过程控制领域出现了许多新的挑战性研究问题.首先综述了非线性分布参数过程(例如材料微结构、颗粒分布、流体流动)的控制、生物系统与生物医学过程的分析与控制、城市污水处理集成监控系统等的最新研究进展以及一些未来的研究方向.其次讨论了解决复杂控制问题所需的一些方法和集成工具,主要包括过程系统工程理论和方法、集成物理装置与通讯网络的控制系统组成等.最后指出了目前控制应用相对薄弱的领域是控制理论与工程界关注的重点.     

汽油调合中双调合头在线协调控制的研究

汽油调合生产存在着用两个调合头生产不同牌号产品的情况.若两调合头使用公用组分并同时进行生产,可能发生争抢公用组分,影响两调合任务完成.为解决这一问题,文章针对两调合任务控制模式组合情况多样的现实.提出了独立于单调合头控制算法的在线协调控制算法.案例仿真结果证明该协调控制算法能够解决两调合头同为配方优化、同为质量反馈控制或分别为质量反馈控制与配方优化时的公用组分争抢问题.协调算法能合理分配公用组分在两调合头中的使用,保证调合任务的顺利完成.     

Optimizing the operating conditions in a high precision industrial process using soft computing techniques

This interdisciplinary research is based on the application of unsupervized connectionist architectures in conjunction with modelling systems and on the determining of the optimal operating conditions of a new high precision industrial process known as laser milling. Laser milling is a relatively new micro‐manufacturing technique in the production of high‐value industrial components. The industrial problem is defined by a data set relayed through standard sensors situated on a laser‐milling centre, which is a machine tool for manufacturing high‐value micro‐moulds, micro‐dies and micro‐tools. The new three‐phase industrial system presented in this study is capable of identifying a model for the laser‐milling process based on low‐order models. The first two steps are based on the use of unsupervized connectionist models. The first step involves the analysis of the data sets that define each case study to identify if they are informative enough or if the experiments have to be performed again. In the second step, a feature selection phase is performed to determine the main variables to be processed in the third step. In this last step, the results of the study provide a model for a laser‐milling procedure based on low‐order models, such as black‐box, in order to approximate the optimal form of the laser‐milling process. The three‐step model has been tested with real data obtained for three different materials: aluminium, cooper and hardened steel. These three materials are used in the manufacture of micro‐moulds, micro‐coolers and micro‐dies, high‐value tools for the medical and automotive industries among others. As the model inputs are standard data provided by the laser‐milling centre, the industrial implementation of the model is immediate. Thus, this study demonstrates how a high precision industrial process can be improved using a combination of artificial intelligence and identification techniques.     

Model-based analysis of the health, safety and environment domain in the process industry

The chemical process industry needs well-defined, engineering-controlled operation procedures to insure the safety of their plant operations and to protect the people working with hazardous materials. Accidents may seriously harm the employees, destroy expensive factory equipment and contaminate and deteriorate the environment of the entire areas. The engineering control can be significantly enhanced through the use of process models for situation analysis. Process models will also provide effective decision support in the plant operation. The objective was to develop in Elf-Atochem a reference model for improving the complex process for implementing and tracking a work permit for people working in plant areas with health, safety and environmental risks. This permit documents all protection and formal authorisations required prior to any work in the hazardous areas of a chemical plant. The model consists of a process model and an information model. It further provides the identification of knowledge required to manage the work permit and to facilitate the automation of a number of activities. The model serves to analyse the process and to define the user requirements for a workflow application program. The methodology CimOsa/rg, which is based on CIMOSA, has been applied together with the modelling tool CimTool to document the requirements model.     

流程工业的组合积分系统及其先进控制

给出了流程丁业中组合积分系统的定义,分析了其特性.基于模型预测控制的基本原理,设计了组合积分系统的先进控制算法,并成功应用于实际工业过程之中,大大提高了控制的精度和经济效益.