Optimal Approaches to Self-Tuning PID Control

Abstract In this paper two recursive algorithms for the automatic tuning of PID controllers are compared. The control strategies are based on the minimization of performance indices, each reflecting the efficiency of set-point tracking and the magnitude of control effort. These cost functions differ in the use of conditional or unconditional averaging over the process stochastics. The adaptive versions of the resulting algorithms are based on the explicit estimation of system parameters. Although the algorithms involve the processing of sampled data, appropriate transformations are used to yield the three continuous-time PID controller parameters.