Data-driven PID gain tuning for unknown impulse disturbance attenuation

Data-driven design approaches based on input-output measurements with no need for help from a plant model have attracted attention from several researchers. We have proposed such a disturbance attenuation Fictitious Reference Iterative Tuning (FRIT) using input-output data generated by a step or impulse disturbance, and showed the effectiveness of the approach through experiments of DC motor control and helicopter attitude control. The present work applies the approach to the experimental data for temperature control. The PID gains are tuned so that temperature of a piece of metal would follow a disturbance reference model output signal. From the experimental result, the disturbance attenuation FRIT is effective for PID gain tuning from closed-loop input and output experimental data generated by a impulse disturbance with unknown magnitude.