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  1. 1
    Active force control with iterative learning control algorithm for a vehicle suspension

    Active force control with iterative learning control algorithm for a vehicle suspension by Rosmazi, Rosli

    Published 2013
    “…The new control scheme named active force control with iterative learning control algorithm (AFCIL) is complemented by the classic proportionalintegral-derivative (PID) control incorporated and designed as the outermost control loop. …”
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  2. 2
    Active Suspension System for Passenger Vehicle using Active Force Control with Iterative Learning Algorithm

    Active Suspension System for Passenger Vehicle using Active Force Control with Iterative Learning Algorithm by Rosmazi, Rosli, Musa, Mailah, Priyandoko, Gigih

    Published 2014
    “…The paper describes the practical implementation of a new hybrid control method to a vehicle suspension system using Active Force Control (AFC) with Iterative Learning (IL) and proportional-integralderivative (PID) control strategy. …”
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  3. 3
    Intelligent adaptive active force control of a robotic arm with embedded iterative learning algorithms

    Intelligent adaptive active force control of a robotic arm with embedded iterative learning algorithms by Mailah, Musa, Ong, Miaw Yong

    Published 2001
    “…The paper highlights a novel and robust method to control a robotic arm using an iterative learning technique embedded in an active force control strategy. …”
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  4. 4
    Intelligent active force control of a rigid robot arm using embedded iterative learning algorithm

    Intelligent active force control of a rigid robot arm using embedded iterative learning algorithm by Mailah, Musa

    Published 2000
    “…The paper presents a novel approach to estimating the inertia matrix of a robot arm adaptively and on-line using an iterative learning algorithm. It is employed in conjunction with an active force control strategy which has been shown to be very effective in accommodating the disturbances. …”
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  5. 5
    Adaptive active force control of a robotic arm employing twin iterative learning algorithms / Musa Mailah and Ong Miaw Yong

    Adaptive active force control of a robotic arm employing twin iterative learning algorithms / Musa Mailah and Ong Miaw Yong by Mailah, Musa, Ong, Miaw Yong

    Published 2004
    “…The paper highlights a novel and robust method to control a robotic arm using iterative learning technique embedded in an active force control strategy. …”
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  6. 6
    Control of a robot arm using iterative learning algorithm with a stopping criterion

    Control of a robot arm using iterative learning algorithm with a stopping criterion by Mailah, Musa, Chong, Jonathan Wun Shiung

    Published 2002
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  7. 7
    Hardware-in-the-Loop Simulation for Active Force Control with Iterative Learning Applied to an Active Vehicle Suspension System

    Hardware-in-the-Loop Simulation for Active Force Control with Iterative Learning Applied to an Active Vehicle Suspension System by Rosmazi, Rosli, Musa, Mailah, Priyandoko, Gigih

    Published 2014
    “…The paper focuses on the practical implementation of a novel control method to an automotive suspension system using active force control (AFC) with iterative learning algorithm (ILA) and proportional-integral-derivative (PID) control strategy. …”
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  8. 8
    Enhancement of impact force determination with modal transformation method by using integration and data filtering /Khoo Shin Yee

    Enhancement of impact force determination with modal transformation method by using integration and data filtering /Khoo Shin Yee by Khoo, Shin Yee

    Published 2013
    “…Additional information about the loads experienced by the structure will aid the development iterations resulting in a better outcome. However, direct measurement by using force transducer is not practical in some cases due to some difficulties in force sensor configuration. …”
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  9. 9
    Adaptive force-position-speed collaborative process planning and roughness prediction for robotic polishing

    Adaptive force-position-speed collaborative process planning and roughness prediction for robotic polishing by Haohao, Ma, As’arry, Azizan, Jing, Niu, Ismail, Mohd Idris Shah, Ramli, Hafiz Rashidi, Zuhri, M. Y.M., Delgoshaei, Aidin

    Published 2025
    “…An adaptive impedance control strategy is implemented to enhance force control, and PD iteration and RBF neural networks are used to ensure stable contact force and accuracy. …”
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  10. 10
    Development of a software for simulating active force control schemes of a two-link planar manipulator

    Development of a software for simulating active force control schemes of a two-link planar manipulator by Mailah, Musa, Poh, Yang Liang

    Published 2005
    “…On Top Of That, The Graphical Results Can Be Observed And Analysed On-Line While The Program Is Running. By Using Matlab And Its Gui Facility, All The AFC Schemes Already Described In The Previous Works Such As The AFC With Crude Approximation Method, AFC And Iterative Learning (Afcail), AFC And Neural Network (Afcann), AFC And Fuzzy Logic (Afcafl), And AFC And Genetic Algorithm (Afcaga) Schemes Were Linked Into A Single Menu-Driven Program Where Each Of The Scheme Can Be Easily Selected And Executed By The User. …”
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  11. 11
    The implications for ahybrid detection technique against malicious sqlattacks on web applications

    The implications for ahybrid detection technique against malicious sqlattacks on web applications by Bahjat Arif, Sarajaldeen Akram, Wani, Sharyar

    Published 2025
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  12. 12
    Simulation of steady mixed convection in a lid-driven cavity filled with newtonian fluid by finite volume method

    Simulation of steady mixed convection in a lid-driven cavity filled with newtonian fluid by finite volume method by Abu Bakar, Norhaliza

    Published 2019
    “…The resultant matrices were then solved iteratively using the Tri- Diagonal Matrix Algorithm coded in FORTRAN90. …”
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  13. 13
    Development of a software for simulating active force control schemes of a two–link planar manipulator

    Development of a software for simulating active force control schemes of a two–link planar manipulator by Mailah, Musa, Poh, Yang Liang

    Published 2005
    “…On top of that, the graphical results can be observed and analysed on–line while the program is running. By using MATLAB and its GUI facility, all the AFC schemes already described in the previous works such as the AFC with crude approximation method, AFC and Iterative Learning (AFCAIL), AFC and Neural Network (AFCANN), AFC and Fuzzy Logic (AFCAFL), and AFC and Genetic Algorithm (AFCAGA) schemes were linked into a single menu–driven program where each of the scheme can be easily selected and executed by the user. …”
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  14. 14
    Development of DNA-based dynamic key-dependent block cipher

    Development of DNA-based dynamic key-dependent block cipher by Saeed, Auday H.

    Published 2015
    “…For the permutation layer the use of key-dependent ransformations and processes inspired by DNA techniques forces the attackers to try and devise hard new frameworks of cryptanalytic mechanisms. …”
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  15. 15
    Development of Finite Element Code for Non-Linear Analysis of Interlocking Mortarless Masonry System

    Development of Finite Element Code for Non-Linear Analysis of Interlocking Mortarless Masonry System by Ahmed Al- Wathaf, Ahmed Hasan

    Published 2006
    “…An incremental-iterative 2-D nonlinear finite element code is developed to implement the proposed algorithm and analyze the masonry system till failure. …”
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  16. 16
    Modeling and multi-objective optimal sizing of standalone photovoltaic system based on evolutionary algorithms

    Modeling and multi-objective optimal sizing of standalone photovoltaic system based on evolutionary algorithms by Ridha, Hussein Mohammed

    Published 2020
    “…The IEM algorithm uses the attraction-repulsion mechanism to change the positions of solutions towards the optimality. …”
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  17. 17
    Multi-objectives process optimization in end milling process of aluminium alloy 6061-T6 using genetic algorithm

    Multi-objectives process optimization in end milling process of aluminium alloy 6061-T6 using genetic algorithm by W., Safiei, Rahman, M. M., M.Y., Ali

    Published 2024
    “…Therefore, this paper aims to obtain optimum conditions of ethe nd milling process for three cutting inserts with multi-objective parameters using a combination of mathematical modelling and genetic algorithm. …”
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  18. 18
    Digital Quran With Storage Optimization Through Duplication Handling And Compressed Sparse Matrix Method

    Digital Quran With Storage Optimization Through Duplication Handling And Compressed Sparse Matrix Method by Ashraf Saleh Mohammad Alomoush

    Published 2024
    thesis::doctoral thesis
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  19. 19
    Non-parametric induction motor rotor flux estimator based on feed-forward neural network

    Non-parametric induction motor rotor flux estimator based on feed-forward neural network by Siti Nursyuhada, Mahsahirun, Nik Rumzi, Nik Idris, Zulkifli, Md. Yusof, Sutikno, Tole

    Published 2022
    “…A forced iteration of 1,000-epochs is imposed in the training process. …”
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  20. 20
    STUDIES ON THE NONLINEAR INTERACTIONS ASSOCIATED WITH MOORED SEMI SUBMERSIBLE OFFSHORE PLATFORMS

    STUDIES ON THE NONLINEAR INTERACTIONS ASSOCIATED WITH MOORED SEMI SUBMERSIBLE OFFSHORE PLATFORMS by NOUR ELFADUL ABBAS, YASSIR MOHAMMEDNOUR ELFADUL ABBAS

    Published 2011
    “…The effects of pretension, mooring line configuration, clump weight, cable unit weight, elongation, breaking strength and pretension angle on the behavior of multi-component mooring line, were investigated by using an implicit iterative solution of the catenary equations. …”
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