Direct PID Tuning from Closed-Loop Data and Its Application to Unstable Processes

Abstract

In the present work, a new practical method for direct tuning of PID controllers using operation data under feedback control is proposed. Conventional direct tuning methods have the following problems: need for iterative experiments and difficulty in properly determining a reference model without information on a process. The objective of this research is to propose Extended Fictitious Reference Iterative Tuning (E-FRIT) for solving these problems through 1) the objective function is modifieded to include the penalty for changes of the input variable, 2) the parameter in the reference model is optimized together with PID control parameters, and 3) particle swarm optimization (PSO) is used to make the first two extensions with facility. The usefulness of the proposed E-FRIT is demonstrated through the case studies of unstable chemical reaction processes.