Design of an Implicit Self-tuning PID Controller based on an Augmented Output

Abstract

PID controllers have been widely employed in real process systems. Since PID gains strongly affect the control performance, lots of schemes for tuning PID gains have been proposed. In processes industries, most of the PID controllers have fixed PID gains. However, it is impossible to obtain good control performance for time-variant systems by the fixed PID controllers. Therefore, it is important to tune PID gains in an on-line manner. In addition, especially in process systems, it is difficult to practice an open-loop experiment. Since, it is important to determine PID gains directly from the closed-loop operating data. In this paper, in order to overcome these problems, an implicit self-tuning PID control scheme is proposed. In the proposed method, a new PID gain tuning law based on an augmented output generated by closed-loop data is introduced, and recursive least squares method is applied to tune the parameters in an on-line manner. The effectiveness of the controller design scheme is evaluated by simulation and experimental examples.