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- W4200571570 abstract "Proportional-Integral-Derivative (PID) controllers are widely used in academia and industry thanks to their simplicity and performance. For nonlinear or unknown systems, they are however not very well suited. Augmenting a PID controller with a neural network adds the abilities to adapt to unknown and learn the dynamics of nonlinear systems. In this paper, two PID neural network controllers (PIDNNC) are simulated, compared and discussed in detail. Based on simulations, one approach is preferred due to its adaptability and I and D gains approaching zero when they are not needed." @default.
- W4200571570 created "2021-12-31" @default.
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- W4200571570 date "2021-11-03" @default.
- W4200571570 modified "2023-10-04" @default.
- W4200571570 title "Comparison Between Two PID Neural Network Controller Approaches - Simulation and Discussion" @default.
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- W4200571570 doi "https://doi.org/10.1109/iccad52417.2021.9638766" @default.
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