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Cited by 14 publications
(10 citation statements)
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“…( 41) can be considered the updating term (h(k) w(k)) from the update rule; Eq. (19). Then, replacing e(k) in Eq.…”
Section: Adaptation Of the Learning Rate Based On The Lyapunov Stabil...mentioning
confidence: 99%
See 1 more Smart Citation
“…( 41) can be considered the updating term (h(k) w(k)) from the update rule; Eq. (19). Then, replacing e(k) in Eq.…”
Section: Adaptation Of the Learning Rate Based On The Lyapunov Stabil...mentioning
confidence: 99%
“…Furthermore, [18] proposed a multiple-input-multiple-output adaptive neural-based PID controller (MIMO-AN-PID) to control a hexacopter, i.e., unmanned aerial vehicles. Recently, in 2018, a contour error identifier based on a neural network is constructed to adapt the three parameters of the PID controller (PID-NNEI) using (15-15-1) neural structure and a hyperbolic tangent activation function that used to control three axes of a computer numerical control (CNC) machine as presented in [19]. In 2020, a PID controller based on an RBF neural network (PID-RBFNN) was introduced for a speed profile control of a subway train using (3-5-3) neural network structure [20].…”
Section: Introductionmentioning
confidence: 99%
“…Neural network based algorithms have reported promising results. 16,[20][21][22][23] Neural network based PID gain update algorithms have been successfully implemented to control a servo motor, 24 computerized numerical control machine tools 21 and so on. In Xia et al, 25 a single neuron PI controller has been developed for the control of the BLDC motor.…”
Section: Introductionmentioning
confidence: 99%
“…The algorithms based on neural network have shown promising results. [17][18][19][20][21] The PID gain updating algorithm based on neural network has been successfully applied to the control of servo motor, 21 computerized numerical control machine tool, 18 etc. In Xia et al, 22 a single neuron PI controller is designed for the control system of BLDCM.…”
Section: Introductionmentioning
confidence: 99%