Intelligent process control with integrated robust multivariable controllers and real-time supervisory knowledge-based systems

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

Response time satisfaction in a real-time knowledge-based system

An intelligent system for multivariate statistical process monitoring and diagnosis

Real-time knowledge-based systems (KBSs) are increasingly used to monitor and control real-time processes. Although a KBS may perform well on the average in terms of computation time, it may fail to deliver results while meeting deadlines in some critical cases. This is not acceptable in a hard real-time system where all timing constraints imposed by the environment must be continuously observed by the embedded computer and the failure to meet a single deadline may be catastrophic. Thus the technology for building a new generation of real-time KBSs must be developed before we can rely on these smart systems to perform complex, safety-critical monitoring and control functions in a real-time environment as we currently do on embedded software programs implemented in procedural languages. In this article, we examine some fundamental issues in the design and development of real-time KBSs including (1) response time analysis, and (2) rule-base optimization and synthesis. >

Towards a temporal coherence management in real-time knowledge-based systems

KJ3—a tool assisting formal validation of knowledge-based systems

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

Computer-Aided Knowledge-Based Monitoring and Diagnostic System for Emulsion Polymerization

Artificial intelligence can assist in industrial control in many ways, but this paper concentrates on the role of knowledge-based systems in the areas of control, detection and diagnosis of faults, scheduling and planning. The paper argues that the application of knowledge-based techniques can provide a unification of these and other activities, and outlines the requirements of knowledge representation and inference techniques that are needed to make such systems a reality. The advances in hardware, including sensors as well as computers, that will be driven by and in turn stimulate the introduction of the knowledge-based industrial control systems are also considered.

Ventricular assist device (VAD) implantation for patients with advanced heart failure as an alternative therapy to heart transplantation has increased patients' survival and quality of life thanks to improvements in the pump's geometry, local and supervisory control systems. Suppose the supervisory control system for these devices is considered an open system, in that case, an approach considers integrating various agents that interact collaboratively to determine the behavior. In addition to the physical device and its local control system, there is the patient and the medical team assisting this patient. In this way, a VAD can be considered a cyber-physical device, in which characteristics such as intelligence, connectivity, and reactivity can be observed. Based on this paradigm, there was a possibility of improvement from the interaction and collaboration between cyber-physical VADs capable of communicating with a supervisory control system. While the local control system is responsible for the device's drive functions, the supervisory system is responsible for managing several local control systems of each VAD. The connectivity between the devices is a fundamental characteristic for the proposal of intelligent VADs, which can offer the multidisciplinary medical team tools to monitor the patient's condition and decision support algorithms that make up the supervisory system. This new context causes an evolution from cyber-physical VADs to an architecture based on Reference Architecture Model for Industry 4.0 (RAMI 4.0) to allow the reconfiguration of VADs in a new paradigm based on Health 4.0.

At the time being knowledge-based systems are used in almost all life aspects. The main reason for trying to use knowledge-based systems in real-time control is to reduce cognitive load on users (overload), their application proving to be important when conventional techniques have failed or are not sufficiently effective [1]. The development of automated diagnosis techniques and systems can help also to minimize downtime and maintain efficient output. This paper presents some issues of applying knowledge-based systems to real-time control systems. It describes and analyzes the main issues concerning the real-time domain and provides possible solutions, such as a set of requirements that a real-time knowledge-based system must satisfy. The paper proposes a possible architecture for applying knowledge-based techniques in real-time control systems. Finally, a way of employing knowledge-based techniques for extending the existing automatic control and monitoring system for the geothermal plant from the University of Oradea is presented.

To date, knowledge-based systems ( KBS's) have been developed on an ad-hoc basis, without the benefit of quantitative tools for analysis and synthesis. If we are to approach the field of knowledge engineering systematically, we must develop performance measures to characterize the effectiveness and efficiency of knowledge systems, and thereby serve to highlight directions for improvement. When KBS's are applied to control tasks, real-time performance becomes critical. Consequently, the internal processes of knowledge-based control systems ( KBCS) must be optimized to fulfill real-time requirements. This article derives relationships between information attributes and system performance. The performance measures are applied to a knowledge-based design system ( KBDS) for the synthesis of KBCS. The performance measures reflect intuitively satisfying properties of the KBDS and provide insights into the system not possible through a straight orward inspection of the program code. This type of system can be use...

This work is concerned with the design and construction of a yarn brushing machine to produce and monitor such yarns by means of the application of knowledge-based, computer vision and on-line control systems. Part I describes an investigation into the effects that input yarn properties and changes in machine parameters have on the characteristics of the brushed yarn.

The numerical modelling and process simulation for the fault diagnosis of rotary kiln incinerator were accomplished. In the numerical modelling, two models applied to the modelling within the kiln are the combustion chamber model including the mass and energy balance equations for two combustion chambers and 3D thermal model. The combustion chamber model predicts temperature within the kiln, flue gas composition, flux and heat of combustion. Using the combustion chamber model and 3D thermal model, the production-rules for the process simulation can be obtained through interrelation analysis between control and operation variables. The process simulation of the kiln is operated with the production-rules for automatic operation. The process simulation aims to provide fundamental solutions to the problems in incineration process by introducing an online expert control system to provide an integrity in process control and management. Knowledge-based expert control systems use symbolic logic and heuristic rules to find solutions for various types of problems. It was implemented to be a hybrid intelligent expert control system by mutually connecting with the process control systems which has the capability of process diagnosis, analysis and control.

The economic aspects of the online, programmable computer for supervisory control of producing operations are discussed. The material presented reflects the performance and economics of a pilot supervisory control installation that has been supervising and controlling producing operations for one year in two widely separated fields in southeastern New Mexico. Expansion of this pilot supervisory system is necessary to obtain an actual payout, but the performance of the pilot project does provide a reliable basis for predicting the economics of full scale computer controlled producing operations. Introduction A pilot installation to evaluate a supervisory, monitoring and control system for properties operated in southeastern New Mexico by Continental Oil Co. was installed in Oct., 1964. The pilot project included 56 wells in two fields to be controlled from the district office in Hobbs, N. M. Results of the pilot project would serve to evaluate the economics of expanding the system to include three additional areas and 326 additional wells in a full scale operation, with possible future expansion to a total of 600 to 700 wells. The pilot installation and three additional areas to be included in the full scale project are shown in Fig. 1.This supervisory control system is similar in concept to an earlier system installed during 1962 in the Big Horn Basin of Wyoming by the Rocky Mountain Region of Conoco. The pilot project has been sufficiently complex to prove equipment capability and performance, but limited enough to keep installation costs within reason should results indicate the total project to be economically unattractive leases in the Hobbs and El Mar fields of New Mexico comprise this two-field pilot project. These areas are separated by approximately 56 air miles (Fig. 1). The Hobbs field, located two miles from the central supervisory in the city of Hobbs, consists of three leases with 14 flowing or pumping wells producing 5 1 8 BOPD into one central tank battery. The El Mar field includes three leases with 42 pumping or flowing wells producing 700 BOPD into a central tank battery. The objective of the pilot program was to determine if a significant portion of the pumper functions could be performed by the supervisory system while maintaining producing efficiency at a level equal to or greater than before. It was recognized that not all of the pumper duties could be performed by computer control but that almost all of the check-and-see type routine could be surveyed by the system. The majority of pumper time involves travel and inspection duties; therefore, it was estimated that approximately 50 per cent of his assignments could be supervised by the control system. JPT P. 48ˆ