Enhancement of DDST-MFAC for tracking performance by using dynamic data reconciliation
Zhiwen Wang,
Amirul Syafiq Sadun,
Mingxu Lv
et al.
Abstract:Model-free adaptive control (MFAC) stands out as an effective data-driven method for addressing nonlinear problems in industrial processes. To maintain good control performance, a data-driven set-point tuning (DDST) method is used to update the virtual set-point of the MFAC system. The DDST-based MFAC (i.e. DDST-MFAC) constantly approaches the target of the process through the nonlinear set-point tuning method. However, due to equipment errors and external interference, industrial sensors often suffer from mea… Show more
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