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Design of an implicit self-tuning PID controller based on a GPC

Theoretical design on self-tuning proportionalintegral-derivative (PID) controller based on generalized predictive control (GPC) with model-free technique is presented in this study, which enables us to deal with the system both with unknown delay time and unknown or time-varying parameters. Currently, in many control design approaches, constructing the model of the plant has been usually regarded as the first step, then a controller is designed based on the identified model. On the one hand, it is difficult to construct the accurate model and the process is time consuming. On the other hand, the control performance is not always desirable with the presence of errors during the identification of model. Hence, utilizing the on-line or off-line data, to directly design controller especially under lack of accuracy of modeling the process, has been gradually received considerable attention in the recently years. And this study will give you an approach to design the control parameters based on GPC directly from the on-line data, and then converting those parameters to PID parameters from the practical point of view. The proposed method is verified by simulation, where the results demonstrate the efficiency of the proposed method.