An Extension of Singular Value Analysis for Assessing Manipulated Variable Constraints

Abstract A new approach called feasible output radius analysis for linear or linearised models is introduced to address the problem of scaling dependency. This problem arises when assessing the effect of manipulated variable constraints (MVCs) on the closed-loop performance of chemical processes prior to carrying out control designs. The new indicators, R and R can be used to rank alternative control schemes on the basis that the larger R and R , the better the closed-loop performance in the presence of control constraints. These indicators are determined from extending the concept of the ‘feasible output amplitude region’ and are independent of the input scaling chosen. Theoretical analysis shows that this method is an extension of the more traditional singular value analysis approach and is more flexible in dealing with various kinds of manipulated variable constraints. A case study, i.e. a two-CSTR process, is investigated using the new method. Via the case study, some superior characteristics of the new technique are demonstrated, such as ease of calculation, and flexibility in coping with different kinds of constraints.