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Discrete‐time prescribed performance controller based on affine data‐driven model
Author(s) -
Treesatayapun Chidentree
Publication year - 2020
Publication title -
international journal of adaptive control and signal processing
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.73
H-Index - 66
eISSN - 1099-1115
pISSN - 0890-6327
DOI - 10.1002/acs.3168
Subject(s) - affine transformation , control theory (sociology) , controller (irrigation) , computer science , nonlinear system , property (philosophy) , fuzzy logic , discrete time and continuous time , data driven , control engineering , fuzzy control system , control (management) , mathematics , artificial intelligence , engineering , philosophy , statistics , physics , epistemology , quantum mechanics , pure mathematics , agronomy , biology
Summary The noncontinuous behavior of the controlled plant occurring as both positive and negative control directions is observed from the prototyping robotic system. By considering the controlled plant as a class of unknown nonlinear discrete‐time systems, the affine data‐driven model (ADM) is developed by a multi‐input fuzzy rule emulated network (MiFREN) when the property of a continuous function is omitted. Therefore, the controller is established by the result of ADM when the specification of tracking error can be designed by the prescribed boundaries. The theoretical principle is utilized for the closed‐loop analysis which guarantees the performance by designing the setting parameters. For the practical aspect, the design procedure and the performance are demonstrated by the experimental results.