Path: Top -> Journal -> Jurnal Internasional -> Fuzzy Information and Engineering -> 2021 -> Volume 13, Issue 3
Output Feedback Controller for a Class of Unknown Nonlinear Discrete Time Systems Using Fuzzy Rules Emulated Networks and Reinforcement Learning
Oleh : C. Treesatayapun, Fuzzy Information and Engineering
Dibuat : 2022-02-16, dengan 0 file
Keyword : Model-free adaptive control, reinforcement learning, nonlinear discrete time systems, fuzzy neural network, DC motor current control
Url : http://www.tandfonline.com/doi/full/10.1080/16168658.2021.1943887
Sumber pengambilan dokumen : web
A model-free adaptive control for non-affine discrete time systems is developed by utilising the output feedback and action-critic networks. Fuzzy rules emulated network (FREN) is employed as the action network and multi-input version (MiFREN) is implemented as the critic network. Both networks are constructed using human knowledge based on IFTHEN rules according to the controlled plant and the learning laws are established by reinforcement learning without any off-line learning phase. The theoretical derivation of the convergence of the tracking error and internal signal is demonstrated. The numerical simulation and the experimental system are given to validate the proposed scheme.
Deskripsi Alternatif :A model-free adaptive control for non-affine discrete time systems is developed by utilising the output feedback and action-critic networks. Fuzzy rules emulated network (FREN) is employed as the action network and multi-input version (MiFREN) is implemented as the critic network. Both networks are constructed using human knowledge based on IFTHEN rules according to the controlled plant and the learning laws are established by reinforcement learning without any off-line learning phase. The theoretical derivation of the convergence of the tracking error and internal signal is demonstrated. The numerical simulation and the experimental system are given to validate the proposed scheme.
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