[PDF] Top 20 Design of radial basis function neural network controller for BLDC motor control system
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Design of radial basis function neural network controller for BLDC motor control system
... Neural network as an intelligent control algorithm, is known for its strong capacities of self-learning, self-adapting and self-organization, and it is suitable for the control of nonlinear ... See full document
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Adaptive fuzzy sliding mode and indirect radial-basis-function neural network controller for trajectory tracking control of a car-like robot
... dynamic design lab ...in system models and also the existence of non-holonomic constraints, the designing of output feedback controllers is a challenging ...adaptive neural controller for ... See full document
14
An Adaptive Controller using Radial Basis Function Neural Network with Reinforcement Learning
... PID controller can perform the tracking control task ...the controller to be tuned properly and at the same time the reinforcement learning itself is a good control strategy especially when ... See full document
7
Research on Intention Recognition Method Based on Radial Basis Function Neural Network
... its controller, and finally realizes the follow motion, resulting in the time delay ...the basis of human-hu- man collaboration, put forward that if a robot is en- dowed with the prejudging ability like ... See full document
11
Designinga Neuro-Sliding Mode Controller for Networked Control Systems with Packet Dropout
... addresses control design in networked control system by considering stochastic packet dropouts in the forward path of the control ...mode controller is utilized to overcome the ... See full document
10
Adaptive sliding mode control with radial basis function neural network for time dependent disturbances and uncertainties
... tracking control. However, this controller is design based on the torque ...proposed controller shows satisfied performance in the case of 2-DOF robot ...manipulators. Radial ... See full document
7
Adaptive Inverse Control of Proton Exchange Membrane Fuel Cell Using RBF Neural Network
... remarkable control demands, due to the inherent nonlinear characteristics and time-varying ...inverse control using radial basis function neural network (RBFNN) to PEMFC ... See full document
13
Maximum energy capture of variable speed variable pitch wind turbine by using RBF neural network and fuzzy logic control
... to control thepitch angle of turbine i.e. pitch control is ...pitch controller, the turbine speeds are controlled as rated ...pitch control. This system of controlling will helps to run ... See full document
8
Neural network controller design for position control system improvement
... DC motor modeling and identifying the problems that exist in its current control such as PID ...DC motor and MATLAB Simulink for implementation in real-time control ... See full document
38
Active Disturbance Rejection Control for a Class of Non affine Nonlinear Systems via Neural Networks
... rejection controller based on radial basis function (RBF) neural network is proposed for a class of non-affine nonlinear systems in this ...rejection control (ADRC) is ... See full document
5
PROPORTIONAL INTEGRAL &DERIVATIVE CONTROLLER FOR BLDC MOTOR
... modern control techniques like fuzzy logic controllers or neural networks controllers, PID controllers constitute an important part at industrial control systems so any improvement in PID ... See full document
13
Design of Hanman Entropy Network from Radial Basis Function Network
... the radial basis function network ...new neural network named as Hanman Entropy Network (HEN) is developed from RBFN based on the Information set theory that deals with ... See full document
17
Radial basis function neural network learning with modified backpropagation algorithm
... fundamental design maps non-linear problem into a high dimension space which turns the problem into a linear ...the network. Gaussian function is used to activate the hidden layer (Qasem and ... See full document
32
Adaptive Control of a DC Motor Using Neural Network Sliding Mode Control
... adaptive neural network sliding mode controller proposed to control a DC motor, so we compare proposed controller with PID, classic SMC and ALNN, The simulation results proved ... See full document
5
Radial basis function neural network for software engineering measures A survey
... of Neural Network, and contains a unique hidden ...The Network topology with a single layer of trainable weights radically decreases the time of ...Pi-Sigma Network provides the highest ... See full document
6
Face Recognition using Rectangular Feature
... In this paper, we generalize the things that are useful for the face detection and recognition based on the rectangular feature. The rectangular feature is used for the face detection purpose and feature extraction. PCA ... See full document
5
STOCK MARKET PREDICTION USING BIO-INSPIRED COMPUTING: A SURVEY
... the neural networks [2] outperforms the statistical techniques because of its capability to follow the nonlinear ...with neural networks make the computation derivative free there by reducing the ... See full document
8
Dynamic Threshold Selection for Sequential Learning in Radial Basis Function Networks
... RBF network cannot be applied to all functions with equal ...RBF network with a constant threshold fails to adapt to similar functions of logarithmically varied ...driven system is able to provide ... See full document
10
Applying ANN, ANFIS, and LSSVM Models for Estimation of Acid Solvent Solubility in Supercritical CO
... In the recent years, supercritical fluid has become one of the interests of chemical engineers and chemists as a novel and extensive applicable technology. The synthesis and generating of nanomaterials and extraction ... See full document
36
Novel Ensemble Neural Network Models for better Prediction using Variable Input Approach
... Artificial Neural Network (ANN) models, namely, Multilayer Perceptron Network (MLPN), Elman Recurrent Neural Network (ERNN), Radial Basis Function Network ... See full document
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