156 Reliable control of chemical processes with a supervisory knowledge-based system

The application of a supervisory knowledge-based system (KBS) to provide robust multivariable control of a chemical reaction process with reduced conservatism is examined. The supervisory KBS is capable of monitoring the process to detect process and control system faults or deteriorating control system performance due to changes in the process behavior or operating conditions. If a fault or change in performance is detected, the KBS formulates and implements the necessary corrective action. Control loop tuning is emphasized. The underlying mechanisms are discussed and validation results, using a rigorous simulation of the chemical reactor process, are presented.< <ETX xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">&gt;</ETX>

ROBUST MULTIVARIABLE CONTROL SYSTEM DESIGNS THROUGH REAL-TIME SUPERVISORY KNOWLEDGE-BASED SYSTEMS

Supervised model-based self-tuning control of fermentation processes is addressed. The diversity, nonlinearity and time-varying nature of these processes make their control a challenging task. Conventional linear (PID) controllers with fixed parameters cannot meet the increasing performance requirements over the whole operating range. In the approach pursued in this research, a local linear model is identified at the current working point by using a limited amount input–output data obtained through an identification experiment. A linear controller is then tuned on the basis of this model. To minimize the intervention into the process operation, this tuning procedure is only initiated if the performance of the current controller deteriorates. To this end, a supervisory expert system is designed whose tasks are to monitor the process performance, design an appropriate identification experiment, validate the obtained model and tune the controller. The supervisory system is based on a combination of a state automaton with a rule-based fuzzy inference system. Experimental results have demonstrated the feasibility of this approach.

Chemical process control textbooks and courses differ significantly from their electrical or mechanical control equivalents. The primary goals of this article are to i) emphasize the distinctly challenging characteristics of chemical processes, ii) present a typical process control curriculum and iii) discuss how chemical process control courses can be revised to better meet the needs of a typical BSc-level chemical engineer. In addition to a review of material covered in a standard process control course, we discuss innovative approaches in process control education, including the use of case studies, distributed control systems in laboratories, identification and control simulation packages, and studio-based approaches combining lecture, simulation, and experiments in the same room. We also provide perspectives on needed developments in process control education.

Compaction quality control in filling construction is of great significance to the stability and durability of the face rockfill dam. The conventional method of quality control mainly relies on manual process control and inspection for a limited number of test holes, which cannot meet the high requirements of modern mechanized construction and schedule anymore, with increasing of scale of face rockfill dams. There is an urgent need to propose a new quality control method of face rockfill dams during the entire compaction process. In this paper, a supervisory system based on GNSS (Global Navigation Satellite System) technology, wireless data communication technology, Internet of things technology, and computer technology is developed to supervise the real-time roller compaction parameters of the working surface including rolling track, rolling times, rolling speed, thickness, and smoothness. The system obtains continuous and high-precision spatial position information of roller compaction machines through GNSS technology and then calculates the roller compaction parameter information. The compaction quality control for the face rockfill dam is achieved through the supervision of roller compaction parameters. The feasibility and robustness of the developed supervisory system are validated by a case study in the face rockfill dam of Shuibuya project in China. The practice shows that the system provides a new and effective method of process control for the construction quality of the roller compaction in dam engineering and realizes real-time, precision, and automatic supervising of roller compaction parameters and ensures better construction quality.

The quality of fine chemical material production is a very important content in chemical production process. It is necessary to do a good job of process control related factors, strengthen the research on relevant characteristics, and further point out the production index of fine chemical industry. In order to ensure the effectiveness of chemical production. In recent years, the rapid development of information technology, including big data, cloud computing, industrial interconnection, mobile interconnection, robot, artificial intelligence and deep learning, has created new opportunities for the upgrading of fine chemical process detection and control technology. Therefore, in-depth analysis and study of the characteristics of fine chemical production process and the current situation and development trend of process parameter detection and control technology, and in-depth study of new fine chemical process measurement and control technology will be necessary to improve the comprehensive automation level of fine chemical process and promote the development of fine chemical production technology which will also produce important economic benefits and technical value.

The complexity of effectively controlling chemical processes, both individual units and entire plants, has been widely recognized in the process systems and control communities in industry and academy. This paper presents an overview of the more recent developments in process identification and control, with particular emphasis on exploratory techniques which are still at a conceptual stage. The impact of some of the recent theoretical developments on practical applications are summarized. We hope this critique and the contributions in this session will provide numerous starting points for a broad range of research efforts in process control.

Analysis of the stability and controllability of chemical processes

In this paper, we present an architecture for a run-to-run supervisory process control system that allows the engineer to tailor the form of control for specific processes. The architecture supports different degrees of control, from model-based control to statistical process control to diagnosis. The architecture is compatible with different techniques for model optimization, data acquisition and analysis, and model adjustment and feedback. A primary feature of this architecture is that engineers can define processes In terms of their desired effects, and use process models that transform those effects into machine settings. We have used object technology as the basis for our design and implementation of the architecture. Object-oriented modeling provides the flexibility required to support the varying degrees of control required in a large-scale manufacturing facility. In this paper, we define the components of the architecture, and describe in detail a process control system that was built with this architecture and used in the Computer Integrated manufacturing (CIM) system built for the Microelectronics Manufacturing Science and Technology (MMST) demonstration facility. Although the architecture was developed for the purpose of controlling semiconductor manufacturing processes, the principles behind the architecture may be applied to the control of any process. >

Process and Production Control Package

This paper presents a novel method for translating Petri Nets, a formal language for modeling concurrent systems, into Ladder Diagrams, the graphical programming language used in Programmable Logic Controllers, specifically for textile chemical mixing applications. This addresses the challenge of efficiently implementing complex control logic, particularly in industrial automation scenarios. The proposed two-phase method first converts the PN model into a State Transition Diagram, simplifying the subsequent translation to LD. The second phase maps the STD onto an LD using rules that maintain system behavior consistency. This approach is particularly relevant to the textile industry, where precise and automated control of chemical mixing processes is crucial for consistent product quality and efficient production. The effectiveness of this method is demonstrated through a case study of a textile chemical mixing application, where accurate mixing ratios and timing are critical. The results show that the generated LD accurately reflects the PN model, ensuring reliable and predictable control of the chemical mixing process. This automated approach improves the precision and efficiency of textile chemical mixing, minimizing errors and optimizing resource utilization. The proposed method offers a practical and efficient solution for implementing automated control systems in textile chemical mixing processes, contributing to enhanced quality control and improved productivity in the textile industry. This approach significantly reduces development time and potential errors, ensuring consistency between design and implementation, leading to more reliable and efficient PLC-based control systems

The fundamentals of industrial automation are based on communication and data monitoring, on realtime control of industrial processes without human interference, with that providing opportunities improvements in various ways in the equipment of industries. This article seeks to propose an advance to the final process of a Drywall Roll Forming Machine through an automated baling system to improve the production process of a Metallurgical Industry. That way, a system was built with conveyor and lift tables by rollers and chains with support of sensors and electrical and pneumatic actuators for its operation. The proposal was carried out and successful through computational simulations, using engineering software based on discrete variables of components and communication of a Virtual PLC (Programmable Logic Controller) and a Supervisory System.

Software for process control—A survey

This article addresses the problem of adaptive control of nonlinear chemical processes with time‐varying dynamics. TheQ‐learning and policy‐iteration algorithms have been considered in the reinforcement learning (RL) framework. The performance of the two algorithms has been tested on highly nonlinear simulated continuous stirred tank reactor (CSTR). Comparison with conventional methods shows that the RL techniques are able to achieve better performance, and robustness against uncertainties. The policy‐iteration algorithm is relatively faster in convergence, and better in robustness. Copyright © 2010 Curtin University of Technology and John Wiley &amp; Sons, Ltd.

Electrical Resistance corrosion probes have been used successfully as chemical process indicators and controls in production plants where conductivity, moisture, and pH controls have previously proven ineffective. Examples showing the effectiveness of corrosion sensors in these uses include (1) the control of an acid-saturated organic neutralization where pH control was ineffective because the organic constituent fouled the pH electrode, (2) a brine recovery column where pH control was inadequate to maintain the brine sufficiently neutral for the removal of organics by stripping in a carbon steel column, (3) an anhydrous acid gas facility where corrosion probes were used to assure the dryness of the gas before it entered a steel distribution system, and (4) an anhydrous halogenated organic production plant where corrosion probes were installed for water detection as well as equipment protection.