Effects of Leading Signals on Metrics of Control Quality Indicators

Abstract

The paper demonstrates the influence of leading variables on the quality evaluation of the operation of univariate control loops of a multi-loop control system used in a 1000 MW power unit. We analyse the course of the setpoint and process values, the calculated value of the control signal and the disturbances values and leading variables. The variables that determine the operating point of the object are used as leading variables. In the case of a power unit, the main leading variable is the power setpoint at which the unit operates. The power setpoint determines the flow of fuel, air and steam—the values of these variables were also considered in the control qualityassessment. Methods based on the characteristics of control signals and error values (residual) are used in the loop control quality assessment. Basic metrics, such as mean error, mean absolute error and mean squared error, are used to analyse the control error. In addition, statistical measures in the form of higher degree moments are applied using the difference in their estimations. The study indicates that once the leading signal values are taken into account during the assessment, the risk of incorrectly interpreting decreased values for the considered indicators is minimized. It is shown that it is important to consider the values of leading variables because they determine the operating point. Particular attention is paid to changes in the leading values since they affect the process conditions. This paper discusses mechanisms that could allow control quality to be monitored both under stable operating conditions and during operating point changes. It is shown that even relatively simple metrics can give very good results when leading signals are considered.

Keywords

• control quality
• quality assessment
• metrics normalization
• error distribution