Rotary Inverted Pendulum Identification for Control by Paraconsistent Neural Network

Rotary Inverted Pendulum Identification for Control by Paraconsistent Neural Network

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Artificial neural networks (ANNs) have been used over the last few decades to perform tasks by learning with comparisons.Fitting input-output models, system beer button down shirts for men identification, control, and pattern recognition are some fields for ANN applications.However, problems involving uncertain situations could be challenging for them.

The family of paraconsistent logics (PL) is a powerful tool that can deal with uncertainty and contradictory information, so getting attention from researchers for its implications and applications in artificial intelligence.This investigation describes a novel activation function reasoned on the paraconsistent annotated logic by two-value annotations (PAL2v) rules, a variation of PL, allowing the design of a new paraconsistent neural ps5 price new jersey net (PNN), applied in model identification for control (I4C) of a closed-loop rotary inverted pendulum (RIP) system.