Control loop performance can be compromised for a number of reasons. Two common sources are poor control valve performance and inappropriate controller tuning. An important component of troubleshooting valve problems and selecting controller tuning constants is to perform dynamic response tests (step tests) usually called bump tests. During the bump test, process data consisting of the Process Variable (PV) and the Controller Output is collected and step changes in the Controller Output are performed using the Controller.
Bump tests serve two main purposes: (i) evaluating control valve dynamic non-linearities, such as backlash, stiction, variable deadtime, etc. which are the usual sources of poor valve performance and (ii) determining a dynamic system model for the process (process model) which is used to calculate controller tuning for the control loop.
Performing bump tests to evaluate control valve performance involves making controller output bumps of 1 % Output or less. Quite a few bump tests are required to evaluate both the control valve performance and the variation in the process model parameters. In practice, a dozen bumps or more ranging in size from as small as 0.1 % Output to as high as 10 % Output depending on the control loop are required to accomplish these tasks. Since the bumps made can be quite small and many bumps are required, hand analysis to determine control loop non-linearities and/or a process model represents a considerable investment in time. Software tools can simplify this task.
Equipment capable of relatively fast data collection and capable of measuring very small changes in both the process variable and controller output is required, in order to evaluate control valve performance and accurately determine a dynamic process model. The equipment must be able to detect changes in measured variables to within about 0.1 % of scale; the A/D converter should resolve the signal to at least 12 bits. The equipment must be able to collect the data fast enough in order to accurately resolve the response time and the deadtime; this typically requires a sample inverval no larger than of 0.1 sec./sample. The distributed control system (DCS) is typically not capable of displaying the data with enough resolution. The DCS may not provide data logging capabilities, so that the process data can be analyzed by other software.
The steps in analyzing the bump tests are as follows. First, the individual bumps are identified for further analysis. Each bump test is analyzed to determine the presence of non-linearities and to determine a dynamic system model representing the response. The bump test results should be summarized in table form. The table summarizes process model parameters and/or comments on the non-linearities present. These tables are very helpful in making controller tuning decisions. If the control loop is in sound condition, performance requirements for the control loop are selected and controller tuning constants are calculated. The final step is to generate a report summarizing the bump test findings, the tuning decisions and the final controller tuning selected.
The Lambda tuning method should be used to calculate controller tuning constants. The Lambda value (i.e. the closed loop time constant) is specified as part of the tuning method. The selection of Lambda determines the speed of response of the control loop in Automatic mode. Care must be taken to select a Lambda value that will result in robust control system response which supports the overall process objectives required.
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