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- W4313011332 abstract "In recent years, the cable-driven planar robot has made fruitful achievements in many fields, but the related researches are scarce yet in the industrial engineering field. In this article, as a powerful tool for solving discrete time-varying problems, the discrete-time recurrent neural network (DTRNN) is extended to drive the cable-driven planar robot for discrete real-time tracking control, which is derived by a new immediate discretization method, and thus, is termed as ID-DTRNN model. Specifically, first, we present the physical structure and mathematical model of the cable-driven planar robot. Then, the new ID-DTRNN model is proposed and applied for driving such cable-driven planar robot, which bases on the a different way of construction of the traditional DTRNN model. Through numerical experiments, the feasibility, validity, and physical reliability of the ID-DTRNN model for discrete real-time tracking control of the cable-driven planar robot are fully verified. In addition, in the real world, physical experiments of the cable-driven planar robot are presented, which successfully promote the development of physical application of the ID-DTRNN model, and fill the gap of such model in the industrial engineering field." @default.
- W4313011332 created "2023-01-05" @default.
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- W4313011332 date "2023-06-01" @default.
- W4313011332 modified "2023-10-03" @default.
- W4313011332 title "Tracking Control of Cable-Driven Planar Robot Based on Discrete-Time Recurrent Neural Network With Immediate Discretization Method" @default.
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- W4313011332 doi "https://doi.org/10.1109/tii.2022.3210255" @default.
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