A Pole Assignment Design Method of Process Control System for Tubular Heat Exchanger

This Paper has first studied the simplified model of tubular heat exchanger which is widely used in the industry and other field.On the basis of reference 2,a new pole assignment design method of pro-cess control system with derivative control action is found.For the above system,the method and the for-mation which calculate the feedback matrix K and gain matrix L is given,and the simulation of the system is made.

Formal Reduction of Interfaces to Large-scale Process Control Systems

A formal methodology is proposed to reduce the amount of information displayed to remote human operators at interfaces to large-scale process control plants of a certain type. The reduction proceeds in two stages. In the first stage, minimal reduced subsets of components, which give full information about the state of the whole system, are generated by determining functional dependencies between components. This is achieved by using a temporal logic proof obligation to check whether the state of all components can be inferred from the state of components in a subset in specified situations that the human operator needs to detect, with respect to a finite state machine model of the system and other human operator behavior. Generation of reduced subsets is automated with the help of a temporal logic model checker. The second stage determines the interconnections between components to be displayed in the reduced system so that the natural overall graphical structure of the system is maintained. A formal definition of an aesthetic for the required subgraph of a graph representation of the full system, containing the reduced subset of components, is given for this purpose. The methodology is demonstrated by a case study.

A master-slave generalized predictive synchronization control for preheating process of multi-cavity hot runner system

As a key component of injection molding,multi-cavity hot runner(MCHR)system faces the crucial problem of polymer melt filling imbalance among the cavities.The thermal imbalance in the system has been considered as the leading cause.Hence,the solution may rest with the synchronization of those heating processes in MCHR system.This paper proposes a’Master-Slave’generalized predictive synchronization control(MS-GPSC)method with’Mr.Slowest’strategy for preheating stage of MCHR system.The core of the proposed method is choosing the heating process with slowest dynamics as the’Master’to track the setpoint,while the other heating processes are treated as‘Slaves’tracking the output of’Master’.This proposed method is shown to have the good ability of temperature synchronization.The corresponding analysis is conducted on parameters tuning and stability,simulations and experiments show the strategy is effective.

Study on the Interactivity of Controlled and Automatic Information Processing in L2 Reading

L2 reading is not only an important channel for people to obtain information and knowledge,but also the main way for people to learn a foreign language.Reading information processing can be divided into controlled processing and automatic processing.Controlled information processing is a conscious and resource-intensive processing model,while automatic information processing is an unconscious and automatic processing model.This study investigates the characteristics and interactivity of controlled and automatic information processing in L2 reading,and explores the roles of controlled and automatic information processing strategies in improving L2 reading ability.The findings are as follows:(a)controlled and automatic information processing is interactive in L2 reading;and(b)the uses of controlled and automatic information processing strategies are beneficial to the improvement of the reading ability of L2 learners.This study has important theoretical and practical value in improving the efficiency of L2 reading teaching and learning.

Optimization study of station track utilization in high-speed railroad based on constraints of control in random origin and process

Purpose-The purpose of this paper is to eliminate the fluctuations in train arrival and departure times caused by skewed distributions in interval operation times.These fluctuations arise from random origin and process factors during interval operations and can accumulate over multiple intervals.The aim is to enhance the robustness of high-speed rail station arrival and departure track utilization schemes.Design/methodologylapproach-To achieve this objective,the paper simulates actual train operations,incorporating the fluctuations in interval operation times into the utilization of arrival and departure tracks at the station.The Monte Carlo simulation method is adopted to solve this problem.This approach transforms a nonlinear model,which includes constraints from probability distribution functions and is difficult to solve directly,into a linear programming model that is easier to handle.The method then linearly weights two objectives to optimize the solution.Findings-Through the application of Monte Carlo simulation,the study successfully converts the complex nonlinear model with probability distribution function constraints into a manageable linear programming model.By continuously adjusting the weighting coefficients of the linear objectives,the method is able to optimize the Pareto solution.Notably,this approach does not require extensive scene data to obtain a satisfactory Pareto solution set.Originality/value-The paper contributes to the field by introducing a novel method for optimizing high-speed rail station arrival and departure track utilization in the presence of fluctuations in interval operation times.The use of Monte Carlo simulation to transform the problem into a tractable linear programming model represents a significant advancement.Furthermore,the method's ability to produce satisfactory Pareto solutions without relying on extensive data sets adds to its practical value and applicability in real-world scenarios.

Formalizing the General Plant for Development of Hybrid Process Control Systems

Many process control systems are a kind of hybrid systems. In order to develop a satisfied control strategy, i. e., to make the whole system satisfy some processing requirements, the knowledge of plant is indispensable. This paper proposes a formal model for the general plant for a kind of process control systems. Based on the model, requirements for the system can be specified from goals, and the controller can be designed according to plant based formal approach . An industrial process control system is used to illustrate our models and methods. Duration Calculus, a real time interval logic, is utilized to specify some characters of the model and development of control program for the exemplified system.

An Expert System in Automatic Gauge Control for Rolling Process

Beacuse the practical mathematic model of rolling process can't be built accurately,this paper established an expert system to control the rolling steels' gauge by adjusting the setup roll open, which combined the experience of theoreticians and operators. The system applied the expression method of rule-skeleton+rule-body', and selected an appropriate non-exact reference model and self-study algorithm. The whole system, including auxiliary routes, is designed in Borland C++. Some experiments on this system have been done, and a good result has been achieved.

Reinforcement Learning in Process Industries:Review and Perspective

This survey paper provides a review and perspective on intermediate and advanced reinforcement learning(RL)techniques in process industries. It offers a holistic approach by covering all levels of the process control hierarchy. The survey paper presents a comprehensive overview of RL algorithms,including fundamental concepts like Markov decision processes and different approaches to RL, such as value-based, policy-based, and actor-critic methods, while also discussing the relationship between classical control and RL. It further reviews the wide-ranging applications of RL in process industries, such as soft sensors, low-level control, high-level control, distributed process control, fault detection and fault tolerant control, optimization,planning, scheduling, and supply chain. The survey paper discusses the limitations and advantages, trends and new applications, and opportunities and future prospects for RL in process industries. Moreover, it highlights the need for a holistic approach in complex systems due to the growing importance of digitalization in the process industries.

DESIGN OF AN EXPERT CONTROL SYSTEM FOR LEACHING PROCESS

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Chemical simulation teaching system based on virtual reality and gesture interaction

Background Most existing chemical experiment teaching systems lack solid immersive experiences,making it difficult to engage students.To address these challenges,we propose a chemical simulation teaching system based on virtual reality and gesture interaction.Methods The parameters of the models were obtained through actual investigation,whereby Blender and 3DS MAX were used to model and import these parameters into a physics engine.By establishing an interface for the physics engine,gesture interaction hardware,and virtual reality(VR)helmet,a highly realistic chemical experiment environment was created.Using code script logic,particle systems,as well as other systems,chemical phenomena were simulated.Furthermore,we created an online teaching platform using streaming media and databases to address the problems of distance teaching.Results The proposed system was evaluated against two mainstream products in the market.In the experiments,the proposed system outperformed the other products in terms of fidelity and practicality.Conclusions The proposed system which offers realistic simulations and practicability,can help improve the high school chemistry experimental education.

AN EXPERT CONTROL SYSTEM FORPURIFICATION PROCESS

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Design and development of expert system for controlling sintering process

The general structure of expert system for controlling sintering process has been proposed. It includes knowledge base, inference engine, data acquisition system, learning system, knowledge base management system, explanation system and so on. The control functions consist of sintering chemical composition control centered on basicity and sintering process state control centered on permeability. The adaptive prediction of sintering chemical composition, the control strategy centered on basicity, the control strategy centered on permeability, the judgement of permeability and the prediction of burn through point were studied. The software of system, which includes about 1 000 expert rules, was successfully applied in off line control of sintering process in a sintering plant.

Integration Between Enterprise Process Monitoring and Controlling System and Enterprise Application

The relationships and the features of integration between Enterprise ProcessMonitoring and Controlling System (EPMCS) and Enterprise Process Related Applications (EPRA) wereanalyzed. An integration architecture centered on EPMCS was presented, in which there were fourlayers to connect from EPMCS to EPRA: EPMCS, application integration layer, transport layer andEPRA, and there were four layers used to etstablish integration: presentation layer, function layer,data layer and system layer. The frameworks to connect EPMCS and EPRA were designed, thatEnterprise-Independent Model (EIM), Enterprise-Specific Model (ESM) and meta-model to describe thesetwo models were defined. The method to integrate data based on XML was designed to exchange datafrom EPMCS to EPRA according to the mapping between EIM and ESM. The approches are suitable forintegrating EPMCS and systems in Product Data Management (PDM), project management and enterprisebusiness management.

EXPERT SYSTEM FOR CONTROLLING THE STATE OF SINTERING PROCESS

In order to control sintering process,improve permeability and stabilize burn through point, a control scheme which combines thermal state with permeability state is proposed, and an expert system for controlling sintering process state is developed, the software which includes about 1000 expert rules is successfully applied to off line control of sintering process.

Research on Technological Process Control Model of Reverse Logistics in Manufacturing System

This paper has found out some important input factors of reverse logistics in manufacturing system throuth analysis and summary,and established four kinds of technological process control models of reverse logistics in manufacturing system according to different processing methods. These models embed each other that form a cubic control system of reverse logistics.

Feeding Control System of Conveyor-belt Based on Image Processing

Based on the real time measurement of the width of coal flow, the method for measuring the width and the relative position of coal flow on a conveyor-belt by image processing was presented. A feeding control system of conveyor-belt was proposed using a fuzzy controller. This control system consists of CCD camera, universal image sampling system, control network and executor. The result shows that the algorithm used in the image processing is simple and efficient, and the measuring error of width is less than 4%.

Application of single neuron adaptive PID controller during the process of timber drying

The paper presents a method of using single neuron adaptive PID control for adjusting system or servo system to implement timber drying process control, which combines the thought of parameter adaptive PID control and the character of neural network on exactly describing nonlinear and uncertainty dynamic process organically. The method implements functions of adaptive and self-learning by adjusting weighting parameters. Adaptive neural network can make some output trail given hoping value to decouple in static state. The simulation result indicates the validity, veracity and robustness of the method used in the timber drying process

Stability in Probability and Inverse Optimal Control of Evolution Systems Driven by Levy Processes

This paper first develops a Lyapunov-type theorem to study global well-posedness(existence and uniqueness of the strong variational solution)and asymptotic stability in probability of nonlinear stochastic evolution systems(SESs)driven by a special class of Levy processes,which consist of Wiener and compensated Poisson processes.This theorem is then utilized to develop an approach to solve an inverse optimal stabilization problem for SESs driven by Levy processes.The inverse optimal control design achieves global well-posedness and global asymptotic stability of the closed-loop system,and minimizes a meaningful cost functional that penalizes both states and control.The approach does not require to solve a Hamilton-Jacobi-Bellman equation(HJBE).An optimal stabilization of the evolution of the frequency of a certain genetic character from the population is included to illustrate the theoretical developments.

Multivariable Decoupling Predictive Control with Input Constraints and Its Application on Chemical Process

A constrained decoupling (generalized predictive control) GPC algorithm is proposed for MIMO (malti-input multi-output) system. This algorithm takes account of all constraints of inputs and their increments. By solving matrix equations, the multi-step predictive decoupling controllers are realized. This algorithm need not solve Diophantine functions, and weakens the cross-coupling of the variables. At last the simulation results demon- strate the effectiveness of this proposed strategy.