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  1. 1
    Neural network based model predictive control for a steel pickling process

    Neural network based model predictive control for a steel pickling process by Kittisupakorn, P., Thitiyasook, P., Hussain, Mohd Azlan, Daosud, W.

    Published 2009
    “…The Levenberg-Marquardt algorithm is used to train the process models. In the control (MPC) algorithm, the feedforward neural network models are used to predict the state variables over a prediction horizon within the model predictive control algorithm for searching the optimal control actions via sequential quadratic programming. …”
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  2. 2
    Development of Quantification Algorithm for Control Valve Stiction

    Development of Quantification Algorithm for Control Valve Stiction by H., Zabiri, A., Maulud, N., Omar, M. , Ramasamy

    Published 2009
    “…In this paper, Neural-network techniques are investigated in the development of a quantification algorithm for control valve stiction. …”
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  3. 3
    An improved maximum power point tracking controller for PV systems using artificial neural network; [Ulepszona metoda ?ledzenia maksymalnej mocy systemu fotowoltaicznego z wykorzystaniem sieci neuronowej]

    An improved maximum power point tracking controller for PV systems using artificial neural network; [Ulepszona metoda ?ledzenia maksymalnej mocy systemu fotowoltaicznego z wykorzys... by Younis M.A., Khatib T., Najeeb M., Mohd Ariffin A.

    Published 2023
    “…MATLAB models for a neural network, PV module, and the classical P&O algorithm are developed. …”
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  4. 4
    Voltage tracking of a DC-DC buck converter using neural network control

    Voltage tracking of a DC-DC buck converter using neural network control by Mohamad Narsardin, Mohamad Adhar

    Published 2012
    “…In order to overcome this main problem, a neural network controller with online learning technique based on back propagation algorithm is developed. …”
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  5. 5
    A meta-heuristics based input variable selection technique for hybrid electrical energy demand prediction models

    A meta-heuristics based input variable selection technique for hybrid electrical energy demand prediction models by ul Islam, B., Baharudin, Z.

    Published 2017
    “…Genetic algorithm and simulated annealing techniques are used to optimize the control parameters of the neural network. …”
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  6. 6
    Speed control of separately excited dc motor using artificial intelligent approach

    Speed control of separately excited dc motor using artificial intelligent approach by Bernard, Albinus

    Published 2013
    “…The mathematical model of the motor and neural network algorithm is derived. The controller consists two parts which is designed to estimate of motor speed and the other is which to generate a control signal for a converter. …”
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  7. 7
    SYSTEMATIC DESIGN OF SIMPLY STRUCTURED COMPENSATOR

    SYSTEMATIC DESIGN OF SIMPLY STRUCTURED COMPENSATOR by FUNG , CHUN TING

    Published 2005
    “…This project aims to develop the algorithm for the tuning method that based on Nyquist Stability Criterion and at later stage build a Neural Network Model to predict the tuning parameters for the PID controller. …”
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  8. 8
    Unified neural network controller of series active power filter for power quality problems mitigation

    Unified neural network controller of series active power filter for power quality problems mitigation by Ghazanfarpour, Behzad

    Published 2013
    “…The first and core unit of the controller utilizes adaptive neural network algorithm to extract fundamental component of the supply voltage and detach the present voltage harmonic. …”
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  9. 9
    Early prediction of dengue outbreak using Artificial Neural Network (ANN) / Muhammad Sirajuddin Ismail

    Early prediction of dengue outbreak using Artificial Neural Network (ANN) / Muhammad Sirajuddin Ismail by Ismail, Muhammad Sirajuddin

    Published 2024
    “…The objective is to develop Dengue Outbreak Prediction System using Artificial Neural Network algorithm and evaluate its performance. …”
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  10. 10
    Development of a Bioinspired optimization algorithm for the automatic generation of multiple distinct behaviors in simulated mobile robots

    Development of a Bioinspired optimization algorithm for the automatic generation of multiple distinct behaviors in simulated mobile robots by Hanafi Ahmad Hijazi, Patricia Anthony

    Published 2006
    “…Results showed that robot controllers could be successfully developed using the POE-MOEA algorithm. …”
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    Research Report
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  11. 11
    Voltage tracking of DC-DC CUK converter using neural network control

    Voltage tracking of DC-DC CUK converter using neural network control by Bidin, Mohamed Noor Azman

    Published 2012
    “…To overcome this problem, a neural network controller with online learning back propagation algorithm is developed. …”
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  12. 12
    Neural network controller design for position control system improvement

    Neural network controller design for position control system improvement by Abdullah, Mohamad Syah Rizal

    Published 2013
    “…Neural network controller develop is proposed to overcome the problem of conventional controller weaknesses. …”
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  13. 13
    Single phase shunt active power filter with simplified ADALINE neural network

    Single phase shunt active power filter with simplified ADALINE neural network by Mohd Zainuri, Muhammad Ammirrul Atiqi, Mohd Radzi, Mohd Amran, Abdul Rahman, Nor Farahaida, Che Soh, Azura, Abd Rahim, Nasrudin

    Published 2014
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  14. 14
    Weeds detection for agriculture using Convolutional Neural Network (CNN) algorithm / Khairun Nisa Mohammad Nasir

    Weeds detection for agriculture using Convolutional Neural Network (CNN) algorithm / Khairun Nisa Mohammad Nasir by Mohammad Nasir, Khairun Nisa

    Published 2024
    “…This project aims to develop a weed detection prototype specifically for agricultural settings by utilizing Convolutional Neural Networks (CNN) algorithm. …”
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  15. 15
    Dynamic modelling of a flexible beam structure using feedforward neural networks for active vibration control

    Dynamic modelling of a flexible beam structure using feedforward neural networks for active vibration control by Tuan Abdul Rahman, Tuan Ahmad Zahidi, As'arry, Azizan, Abdul Jalil, Nawal Aswan, Raja Ahmad, Raja Mohd Kamil

    Published 2019
    “…In conclusion, the development of a non-parametric model of the flexible beam structure was conducted and validated for future investigations on active vibration control techniques.…”
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  16. 16
    A modified digital hysteresis and artificial neural network (ANN) algorithms in single phase shunt active power filter control

    A modified digital hysteresis and artificial neural network (ANN) algorithms in single phase shunt active power filter control by Sabo, Aliyu, Abdul Wahab, Noor Izzri, Mohd Radzi, Mohd Amran, Mailah, Nashiren Farzilah, Abdul Rahman, Nor Farahaida

    Published 2014
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  17. 17
    Design and implementation of a real-time adaptive learning algorithm controller for a 3-DOF parallel manipulator / Mustafa Jabbar Hayawi

    Design and implementation of a real-time adaptive learning algorithm controller for a 3-DOF parallel manipulator / Mustafa Jabbar Hayawi by Hayawi, Mustafa Jabbar

    Published 2015
    “…The results of the proposed controller were compared with direct inverse neural controller DINC. …”
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  18. 18
    Development of an Adaptive Algorithm for Solving the Inverse Kinematics Problem for Serial Robot Manipulators

    Development of an Adaptive Algorithm for Solving the Inverse Kinematics Problem for Serial Robot Manipulators by T. Hasan, Ali

    Published 2005
    “…In order to overcome the drawbacks of some control schemes, which depends on modeling the system being controlled, and to overcome the problem of inverse kinematics which are mainly singularities and uncertainties in arm configuration. …”
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  19. 19
    Brain Machine Interface Controlled Robot Chair

    Brain Machine Interface Controlled Robot Chair by Hema Chengalvarayan, Radhakrishnamurthy

    Published 2010
    “…The BMI controls the joystick of the robot chair using a shared control algorithm. …”
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  20. 20
    Design and Implementation of a Voltage Tracking with Artificial Neural Network Controller for a Double-input Buck-Boost Converter

    Design and Implementation of a Voltage Tracking with Artificial Neural Network Controller for a Double-input Buck-Boost Converter by Buswig, Yonis.m, Al-Khalid, Hj Othman, Norhuzaimin, Julai, Sy Yi, Sim

    Published 2017
    “…The neural network controller design, which is developed against output voltage command tracking is proposed. …”
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