Design of an Implicit GMV-PID Controller Using Closed Loop Data

Abstract

SUMMARY In industrial processes, PID control has been applied in many real systems. The control performance strongly depends on the PID parameters. Although some schemes for tuning PID parameters have been proposed, these schemes need system parameters which are estimated by system identification in order to calculate the PID parameters. On the other hand, model-free controller design schemes represented by virtual reference feedback tuning (VRFT) or FRIT have received much attention in the last few years. These methods can calculate control parameters using closed loop data and are expected to reduce computational costs. In this paper, a type of implicit PID controller using closed loop data is proposed. In the proposed method, the PID parameters are calculated on the basis of the implicit generalized minimum variance control. The control performance can be suitably adjusted by means of only a user-specified parameter. The effectiveness of the proposed method is numerically and experimentally evaluated.