Ce Hao, Yueling Wang, Hongbin Wang, and Zhen Zhou
Data-driven control, dynamic linearization, estimation error ob-server, model-free adaptive control, time-varying trajectory tracking
In this study, a data-driven model-free adaptive control (MFAC) approach is proposed based on a new dynamic linearization technique for non-linear discrete-time systems. The advantage of the approach is that the estimation error of the pseudo-partial-derivative (PPD) parameter matrix of compact form dynamic linearization (CFDL) in the dynamic data model is regarded as an equivalent disturbance term, which is estimated by an estimation error observer (EEOB). Particularly, the controller designing only depends on the input/output (I/O) data of the controlled systems. The asymptotic convergence is guaranteed by The MFAC strategy for a slow time- varying trajectory tracking. The simulation results demonstrate the effectiveness of the proposed method.
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