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

Journal from gdlhub / 2022-02-16 15:31:18
By : C. Treesatayapun, Fuzzy Information and Engineering
Created : 2022-02-16, with 0 files

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
Document Source : 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 IF–THEN 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.

Description Alternative :

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 IF–THEN 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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