By Topic

Advanced Process Control Applications for Industry Workshop, 1999. IEEE Industry Applications Society

Date 29-30 April 1999

Filter Results

Displaying Results 1 - 16 of 16
  • IEEE Industry Applications Society. 1999 Advanced Process Control Applications for Industry Workshop. Record of Workshop Papers

    Save to Project icon | Request Permissions | PDF file iconPDF (52 KB)  
    Freely Available from IEEE
  • Table of contents

    Page(s): 0_6
    Save to Project icon | Request Permissions | PDF file iconPDF (31 KB)  
    Freely Available from IEEE
  • Authors index

    Page(s): 0_8
    Save to Project icon | Request Permissions | PDF file iconPDF (23 KB)  
    Freely Available from IEEE
  • Spatial loopshaping tuning for consistency profile control

    Page(s): 50 - 57
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (384 KB)  

    In this paper, recent developments in control of spatially-invariant processes are applied to an industrial problem of cross-directional profile control in papermaking. The process is approximated in terms of a spatial frequency decomposition which allows the extension of traditional techniques of loopshaping to the two-dimensional dynamical and spatial frequency domain. The designed controller is implemented on a real industrial profile control system and demonstrates the performance predicted by the design View full abstract»

    Full text access may be available. Click article title to sign in or learn about subscription options.
  • Vibration control of circular saws

    Page(s): 30 - 38
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (452 KB)  

    Vibration control has been identified by wood products industry as one of the key technologies for increasing wood recovery in wood machining. This paper presents results of a research project for active vibration control of circular saws using magnetic actuators. An active control system was developed to increase wood recovery by reducing saw blade vibration. The displacement and acceleration of different vibration modes were estimated online by a Kalman filter based state estimator. A state feedback controller design was then implemented online and good damping results were achieved View full abstract»

    Full text access may be available. Click article title to sign in or learn about subscription options.
  • Using transient models of liquid pipelines

    Page(s): 39 - 44
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (352 KB)  

    Trans Mountain owns and operates approximately 1300 km of pipelines in Alberta, British Columbia and Washington state. These pipelines transport a variety of liquids including crude oils, refined products and methyl tertiary butyl ether. They traverse both very remote areas and highly populated ones, as well as hundreds of creek, stream, and river crossings. Environmental concerns have led us to construct a number of transient models to assist our monitoring of the pipeline hydraulics and to provide early warning in the unlikely event that we have a leak. These models have also proved useful with the design of our facilities and for training our control centre operators View full abstract»

    Full text access may be available. Click article title to sign in or learn about subscription options.
  • Application of adaptive control to gold processing plant

    Page(s): 65 - 74
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (540 KB)  

    An adaptive control system utilizing neural network modeling and genetic algorithms has been successfully installed and tested in a gold processing plant located in Nevada. The principle design parameter of the system was feedrate improvement. After installation and commissioning, the system was able to pay for itself through increased feedrate within two weeks. The control system, utilizing a self-learning/adapting expert system shell, uses an expert system rule base written with both crisp and fuzzy logic rules complemented by continually updated predictors, and optimizers. Using a genetic algorithm-based selection process, the system is able to select among multiple competing neural network models and the expert system rules to provide optimum performance under continually varying input conditions. The paper describes the installation, rule, predictor, and optimizer configuration, and statistically verifiable testing of the control system, and the resultant performance improvements in an operating plant View full abstract»

    Full text access may be available. Click article title to sign in or learn about subscription options.
  • Using expert systems technology as a real-time optimization tool

    Page(s): 15 - 19
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (316 KB)  

    The management of electric submersible pumps (ESPs) at well sites can be improved using expert system technology to combine real-time sensor information with production engineering rules. When abnormal conditions exist on an artificial lift well, the problem is not always evident until significant production loss and/or pump damage become apparent. By applying expert system technology, operators see the well performance in relation to the pump manufacturers' operating limits in real time. Well performance and production is optimized once the operating constraints are known. Real-time analysis and expert rules provide early warnings of well production difficulties and permit pro-active corrective measures. The expert application described was written for production at ARCO Alaska's West Sak field. The primary objective was to reduce operating and maintenance costs by providing virtual operations assistance so that new wells could be operated and optimized using existing operations personnel View full abstract»

    Full text access may be available. Click article title to sign in or learn about subscription options.
  • Adaptive process control of an acetic acid reactor

    Page(s): 45 - 49
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (240 KB)  

    This paper describes how QuickStudyTM, a model based adaptive process controller, was used to solve a key control problem associated with an acetic acid reactor. The operating company had achieved greater production rates and efficiency through the use of an improved catalyst but with the penalty of decreased reactor temperature stability. A PID based control strategy became unstable at high unit throughput resulting in reduced production rates and lower sustained throughput. The search for a suitable control solution was complicated by the fact that the reactor temperature was open loop unstable and therefore could not be “bump tested”. QuickStudyTM was used successfully to improve controllability without disrupting production. Reactor temperature standard deviation was reduced from 3.6 to 0.8 and sustained throughput was increased by over 5%. Investment payback was less than 2 months. QuickStudy has been performing reliably in this application for over 2 years View full abstract»

    Full text access may be available. Click article title to sign in or learn about subscription options.
  • OPC-simple software integration for legacy systems

    Page(s): 9 - 14
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (196 KB)  

    This paper discusses the use of OLE for process control as a medium for connection of third-party applications to legacy control systems. This topic is becoming more important as legacy system users attempt to “open up” their systems to third-party applications. Several approaches to implementing the OLE for process control interface to existing systems are discussed, including emulation of field hardware, use of available communication ports, and legacy application nodes. The advantages and disadvantages of implementing each approach are discussed, including feasibility, performance and cost. A brief overview of the client-server paradigm is provided, as this is the cornerstone of OLE for process control communications. Finally, some examples of successful connections to legacy systems are presented View full abstract»

    Full text access may be available. Click article title to sign in or learn about subscription options.
  • Advanced thickener control

    Page(s): 83 - 86
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (220 KB)  

    Thickener control is a complex process and a workable expert control system that could be applied across a range of applications has not been available. With the developments in expert control software, combining the latest process control technologies with new artificial intelligence computing tools, thickener control can be greatly simplified. The paper details the implementation of a thickener expert control system at Cortez Gold in Nevada using KnowledgeScapeTM expert control software. Input by a number of thickener experts was used to devise a robust rule based control scheme. The benefits realized from the expert control systems so far have been tighter control of output objectives (e.g. underflow density) and fewer emergency conditions in the thickener. The system architecture and some of the design challenges are discussed View full abstract»

    Full text access may be available. Click article title to sign in or learn about subscription options.
  • Applications of multivariate statistics at Dofasco

    Page(s): 27 - 29
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (160 KB)  

    Multivariate statistical technologies, the principal components analysis and projection to latent structures, are data modeling technologies based on advanced multivariable statistical methods. These methods are capable of: analyzing process data; building predictive models and providing SPC functionality by extracting information from all process and quality data from an operation simultaneously. Multivariate statistical methods are especially powerful techniques for analyzing industrial data sets that have the following characteristics: higher dimensionality; high collinearity; noisy; and with some missing data. The application of these methods have been successfully done at Dofasco since 1993 to analyze data for a variety of purposes, develop online predictive models, and develop online process monitoring systems. An online application is described to illustrate the advantages of this technology View full abstract»

    Full text access may be available. Click article title to sign in or learn about subscription options.
  • NT for soft real time control

    Page(s): 1 - 8
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (412 KB)  

    The key driver for open software based controls, is the ability for products from multiple vendors from both inside and outside the industrial control arena to coexist and integrate on the same platform. Potential users are faced with a critical decision regarding the operating system strategy for open PC-architecture-based-control. Various alternatives exist in the marketplace ranging from real-time operating systems, through operating system extenders, to standard PC operating systems. Much information has been published concerning these alternatives, some without scrutiny of the alternatives, some without understanding of basic operating system behavior and some to justify limited product offerings. This paper reviews the definitions of real time control and discusses the implementation of control solutions using standard Microsoft Windows NT, and its advantages and disadvantages View full abstract»

    Full text access may be available. Click article title to sign in or learn about subscription options.
  • Advanced process control for moisture monitoring and control applications

    Page(s): 58 - 64
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (344 KB)  

    This paper describes the use of advanced process control and sensing technologies for product moisture monitoring and control within industrial process applications. The application of the generic model-based control strategy, an advanced process control technique, in conjunction with online moisture sensors will be shown to provide substantial benefits and superior control results. These technologies are reviewed and applied, with results obtained from a food processing facility. The application of the presented moisture monitoring and control solution to other industrial environments is also given View full abstract»

    Full text access may be available. Click article title to sign in or learn about subscription options.
  • An adaptive artificial neural network to model a Cu/Pb/Zn flotation circuit

    Page(s): 75 - 82
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (376 KB)  

    We describe the planning and development of an artificial neural network model of line 3 of the Copper/Lead/Zinc flotation circuit at Brunswick Mining's concentrator at Bathurst, New Brunswick. The prototype model predicts the copper and lead assays of the concentrate streams of this rougher flotation circuit. In the model, the actual values and rates of change in the main process variables such as head grades, reagent addition, mass flow, density, pH, temperature, cell level and grind size are treated as inputs. The global error in both training and testing of the model is used to indicate the accuracy of the model. The model is fully adaptable, i.e., it can be updated when required to account for ore and/or processing changes that are not currently included in the ANN because of lack of instrumentation or reliability of measurements. The adaptation algorithm is used to select current data to replace records in the existing training and testing datafile. Retraining is conducted whenever the model accuracy declines to a pre-defined target value. The algorithm determines the frequency of retraining. The final system will be expanded to calculate a total of 12 assays using a separate ANN model for each. All models are independently updated. This approach to artificial neural networks provides plant engineers with a process model that is always current and reasonably accurate. Model access provides flexibility in adjusting set-points to achieve increased efficiency in the control of process variables View full abstract»

    Full text access may be available. Click article title to sign in or learn about subscription options.
  • A new generation of adaptive model based predictive controllers applied in batch reactor temperature control

    Page(s): 20 - 26
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (332 KB)  

    Temperature control of processes that involve the heating and cooling of a closed batch reactor can be a real problem for conventional PID based loop controllers. Tuning can be extremely difficult due to the reduced stability margins proved for these types of processes. This paper describes the application of a new advanced process controller that is designed to handle integrating-type processes with long dead times and long time constants. The results described demonstrate that reactors that could previously only be operated manually can be easily automated using model predictive control technology. The barrier to automation of the reactor batch controls can be removed, resulting in the opportunity for improvements in batch consistency, reduced batch cycle times, and improved productivity View full abstract»

    Full text access may be available. Click article title to sign in or learn about subscription options.