Control loop performance monitoring

Abstract

Abstruct-Control loop monitoring can be used to improve the performance of processes in industry. The monitoring tools presented are concerned with reducing the output variance of regulation loops; As a result, three different estimators are used to determine the minimum achievable output variance, the time delay and the static input-output relationship of the process. These three properties can be used together or individually to provide insights into the process. Once the methods are introduced and their algorithms outlined, the monitoring tools are tested on data from industrial processes. These results show the capabilities and limitations of the proposed estimation methods and the potential benefits to be obtained from monitoring.

Performance assessment of cascade control loops

“…Methodologies for the estimation of the best achievable performance bound in terms of output variance have been established for SISO con-Ž trol systems Harris, 1989;Desborough and Harris, 1992; . Stanfelj et al, 1993;Lynch and Dumont, 1996;Kozub, 1997 Ž and MIMO control systems Harris et al, 1996;Huang et al, . 1997 .…”

Minimum-Information-Entropy-Based Control Performance Assessment

“…In addition, there are also some other methods to estimate the minimum variance, such as the processes and disturbances completely identification method, the filtering and correlation analysis method [21], the recursive least squares method [22]. With the estimation of the minimum variance, the upper bound of the MIE can be obtained by (17).…”

Minimum variance in fast, slow and dual‐rate control loops

“…Thus the generalized models of the lifted DR rate and SSR rate can be obtained from (10) and (12). For the FSR, DR and SSR control loops, we design the optimal controllers, calculate the minimum cost functions and then do simulations.…”

“…It is known that the minimum variance (MV) control is the best possible control in the sense that no controllers can provide a lower variance for linear systems with time delays. Many papers [9][10][11][12][13] have shown that MV is a useful benchmark to assess control-loop performance. A significant one is Reference [9] which presented a new direction and framework for the control-loop performance-monitoring area.…”