Model-Based Tuning Methods for PID Controllers
ABSTRACT: The manner in which a measured process variable responds over time to changes in the controller output signal is fundamental to the design and tuning of a PID controller. The best way to learn about the dynamic behavior of a process is to perform experiments, commonly referred to as "bump tests." Critical to success is that the process data generated by the bump test be descriptive of actual process behavior. Discussed are the qualities required for "good" dynamic data and methods for modeling the dynamic data for controller design. Parameters from the dynamic model are not only used in correlations to compute tuning values, but also provide insight into controller design parameters such as loop sample time and whether dead time presents a performance challenge. It is becoming increasingly common for dynamic studies to be performed with the controller in automatic (closed loop). For closed loop studies, the dynamic data is generated by bumping the set point. The method for using closed loop data is illustrated. Concepts in this work are illustrated using a level control simulation.
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Reducing Energy Cost through Improved Disturbance Rejection
ABSTRACT: Two of the most popular architectures for improving regulatory performance and increasing profitability are 1) cascade control and 2) feed forward with feedback trim. Both architectures trade off additional complexity in the form of instrumentation and engineering time for a controller better able to reject the impact of disturbances on the measured process variable. These architectures neither benefit nor detract from set point tracking performance. This paper compares and contrasts the two architectures and links the benefits of improved disturbance rejection with reducing energy costs in addition to improved product quality and reduced equipment wear. A comparative example is presented using data from a jacketed reactor process.
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Performance Monitoring Fundamentals: Demystifying Performance Assessment Techniques
ABSTRACT: Real-time performance monitoring to identify poorly or under-performing loops has become an integral part of preventative maintenance. Among others, rising energy costs and increasing demand for improved product quality are driving forces. Automatic process control solutions that incorporate real-time monitoring and performance analysis are fulfilling this market need. While many software solutions display performance metrics, however, it is important to understand the purpose and limitations of the various performance assessment techniques since each metric signifies very specific information about the nature of the process. This paper reviews performance measures from simple statistics to complicated model-based performance criteria. By understanding the underlying concepts of the various techniques, readers will gain an understanding of the proper use of performance criteria. Basic algorithms for computing performance measures are presented using example data sets. An evaluation of techniques with tips and suggestions provides readers with guidance for interpreting the results.
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Evolving Best-Practices through Simulation-Based Training: Training the Field Operator of the Future
ABSTRACT: Simulators are widely recognized as essential to process control training as they facilitate the propagation of a company's standard operating procedures (SOPs). This paper explores the use of process control simulators by Chevron Products Company to challenge existing corporate SOPs and to help achieve improvements in overall production performance.