Estimation of Variance Reduction Opportunities Through Cascade Control

Abstract

We describe an approach that is useful in deciding if significant benefits, in terms of control loop performance index (through variability reduction), will be achieved by a change in control loop configuration from simple feedback (SFB) to cascade control. The problem is considered in a stochastic setting and solved using the variance decomposition technique. The proposed methodology requires only routine operating data from an existing simple feedback control loop and knowledge of the process delays. Several simulation examples and one experimental case study exemplify the utility of this approach.

Minimum Variance Benchmark for Performance Assessment of Decentralized Controllers

“…Using the concept of interactor matrices, Harris et al and Huang et al proposed the MV benchmark for multiple-input multiple-output (MIMO) systems. This methodology has also been extended to different controller architectures including feedback/feedforward controllers, , cascade controllers , and constrained model predictive controllers, and process types such as linear time varying processes , and nonlinear processes. − The success of the MV benchmark for controller performance assessment is highlighted by its incorporation into a number of industrial software that are used routinely in process industries. , …”

Design and analysis of structured controllers

“…Using the concept of interactor matrices [24], Harris et al [34] and Huang et al [46] proposed MV benchmark for multi-input multi-output (MIMO) systems. This methodology has also been extended to different controller architectures including feedback/feedforward controllers [18,47], cascade controllers [67,71] and constrained model predictive controllers [37], and process types such as linear time varying processes [43,148] and nonlinear processes [25,36].…”