A data-driven improvement for the bio-intelligent neuroendocrine ultra-shot feedback controller

Since building the neuroendocrine ultra-shot feedback controller (NUC) relies too much on a specific model of the plant, it is unsatisfactory to use it when the model is of inaccuracy or unknown. In this paper, inspired by a well known data-driven control algorithm - virtual reference feedback tuning (VRFT), the data-driven NUC (DNUC) method achieves a model-free tuning for NUC and provides a well-performance control. Simulation experiment is taken on a servo motor and the results show that the proposed DNUC method is effective.