Design and experimental evaluation of a data-oriented multivariable PID controller

Abstract

PID control has been applied in many real systems. The control performance strongly depends on PID parameters. Although, some schemes for tuning PID parameters have been proposed, these schemes require system parameters which are estimated by system identification in order to calculate PID parameters. Moreover, most process systems are multivaliable systems which have interference of each respective inputs. On the other hand, data-oriented controller design schemes represented by 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. However, these methods have not been extended for MIMO systems. In this paper, a type of data-oriented multivariable PID controller using closed loop data is proposed. According to the proposed method, full matrices PID parameters which suppress mutual interference are calculated based on the implicit GMVC. Moreover, the control performance can be suitably adjusted by user-specified parameters. The effectiveness of the proposed method is numerically and experimentally evaluated.