Evolutionary Design of a PID Controller Using Closed-loop Data

Abstract

PID control is a common and an effective approach in process control represented by oil plants and chemical plants. However, it is important to determine suitable PID gains included in the PID controller because the control performance strongly depends on these PID gains. Lots of PID tuning methods have been proposed up to now, however, the computed PID gains cannot be employed directly for real plants. In addition, the system model is required in computing PID gains, and the accuracy of the model influences to the control performance. In this paper, a new design scheme of PID controllers without using the system model in computing PID gains. That is, PID gains can be derived by using only the operating (input/output) data. Concretely, the generalized output is newly derived from the PID control law, and the PID gains are computed by using the genetic algorithm so that the generalized output approaches to the system output. As a result, the suitable PID gains can be obtained, which the system output approaches to the reference model output. Finally, in order to illustrate the effectiveness of the proposed scheme, some simulation examples are discussed.