Design of a Data-Driven Model-Free Type GMV-PID Control System for Nonlinear Systems

Abstract

PID control has been widely used in industrial processes. PID gains tuning schemes have been proposed in many ways because these gains have great influence on the control performance. Moreover, lots of PID gains tuning schemes depend on system parameters which are estimated by the system identification. As part of this trend, the model-free controller design schemes which can determine PID gains without employing the system identification have atracted attention. These methods can reduce the calculation cost because it use only closed-loop data. As one of them, authors have proposed a design scheme of GMVC(Generalized Minimum Variance Control) based PID controllers(GMV-PID) which directly computes PID gains using the closed-loop data.
In this paper, the GMV-PID controller design is extended to nonlinear systems. Concretely, in order to cope with nonlinear components, the data-driven approach is introduced. The effectiveness of the proposed scheme is numerically evaluated on a simulation example.