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  1. 1
    Fast and optimal tuning of fractional order PID controller for AVR system based on memorizable-smoothed functional algorithm

    Fast and optimal tuning of fractional order PID controller for AVR system based on memorizable-smoothed functional algorithm by Ren Hao, Mok, Ahmad, Mohd Ashraf

    Published 2022
    “…Therefore, this study proposes a modified smoothed function algorithm (MSFA) based method to tune the FOPID controller of AVR system since it requires fewer number of function evaluation per iteration. …”
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  2. 2
    Optimal power flow using the Jaya algorithm

    Optimal power flow using the Jaya algorithm by Warid, Warid, Hizam, Hashim, Mariun, Norman, Abdul Wahab, Noor Izzri

    Published 2016
    “…Unlike other population-based optimization methods, no algorithm-particular controlling parameters are required for this algorithm. …”
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  3. 3
    Online DE optimization for Fuzzy-PID controller of semi-active suspension system featuring MR damper

    Online DE optimization for Fuzzy-PID controller of semi-active suspension system featuring MR damper by Ahmed, Hesham, As’arry, Azizan, Hairuddin, Abdul Aziz, Hassan, Mohd Khair, Liu, Yunyun, Onwudinjo, Erasmus Cufe Ujunwa

    Published 2022
    “…However, in the Fuzzy-PID controller, the fuzzy logic algorithm is used to auto-tune the PID controller, but it cannot be considered as a fully real-time controller since the fuzzy algorithm uses a previous knowledge base built offline. …”
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  4. 4
    OPTIMIZATION OF HYBRID-FUZZY CONTROLLER FOR SERVOMOTOR CONTROL USING A MODIFIED GENETIC ALGORITHM

    OPTIMIZATION OF HYBRID-FUZZY CONTROLLER FOR SERVOMOTOR CONTROL USING A MODIFIED GENETIC ALGORITHM by WAHYUNGGORO, OYAS WAHYUNGGORO

    Published 2011
    “…Many tuning methods for PID controller have been developed, and one of them is based on natural evolution, the genetic algorithm (GA). …”
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  5. 5
    Process Planning Optimization In Reconfigurable Manufacturing Systems

    Process Planning Optimization In Reconfigurable Manufacturing Systems by Musharavati, Farayi

    Published 2008
    “…The five (5) AADTs include; a variant of the simulated annealing algorithm that implements heuristic knowledge at critical decision points, two (2) cooperative search schemes based on a “loose hybridization” of the Boltzmann Machine algorithm with (i) simulated annealing, and (ii) genetic algorithm search techniques, and two (2) modified genetic algorithms. …”
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  6. 6
    Development of optimization Alghorithm for uncertain non-linear dynamical system

    Development of optimization Alghorithm for uncertain non-linear dynamical system by Abdul Aziz, Mohd. Ismail, Yaacob, Nazeeruddin, Mohd. Said, Norfarizan, Hamzah, Nor Hazadura

    Published 2004
    “…Based on the results of these simulations, we compared the number of iterations needed by each algorithm to arrive at the optimal solution and the CPU time taken for each algorithm to execute the search. …”
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    Monograph
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  7. 7
    Simulated real-time controller for tuning algorithm using modified hill climbing approach

    Simulated real-time controller for tuning algorithm using modified hill climbing approach by Ahmed, Ahmed Abdulelah

    Published 2014
    “…Often, it is necessary to calibrate a certain parameters of a control system due to plant parameters fluctuation over time.In this research, an intelligent algorithmic tuning technique suitable for realtime system tuning based on hill climbing optimization algorithm and model reference adaptive control system (MRAC) technique is proposed. …”
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  8. 8
    PID CONTROLLER TUNING OF 3-PHASE SEPARATOR IN OIL & GAS INDUSTRY USING BACTERIA FORAGING OPTIMIZATION ALGORITHM

    PID CONTROLLER TUNING OF 3-PHASE SEPARATOR IN OIL & GAS INDUSTRY USING BACTERIA FORAGING OPTIMIZATION ALGORITHM by HO JOON , HENG

    Published 2012
    “…So, this paper will introduce Bacterial Foraging Optimization Algorithm (BFOA) in optimizing the parameters for PI control. …”
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  9. 9
    Optimization and control of hydro generation scheduling using hybrid firefly algorithm and particle swarm optimization techniques

    Optimization and control of hydro generation scheduling using hybrid firefly algorithm and particle swarm optimization techniques by Hammid, Ali Thaeer

    Published 2018
    “…To deal with these problems, this thesis introduces three approved intelligent controllers for hydropower generation. Firstly, a hybrid algorithm namely firefly particle swarm optimization (FPSO) and series division method (SDM) based on the practical swarm optimization and the firefly algorithm is proposed. …”
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  10. 10
    Optimum grouping in a modified genetic algorithm for discrete-time, non-linear system identification

    Optimum grouping in a modified genetic algorithm for discrete-time, non-linear system identification by Jamaluddin, Hishamuddin, Abd. Samad, M. F., Ahmad, Robiah, Yaacob, M. S.

    Published 2007
    “…One of the strategies applied is the modified genetic algorithm which relies on, among other things, the separation of the population into groups where each group undergoes mutual recombination operations. …”
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  11. 11
    Optimum grouping in a modified genetic algorithm for discrete-time, non-linear system identification

    Optimum grouping in a modified genetic algorithm for discrete-time, non-linear system identification by Jamaluddin, H., Samad, M. F. A., Ahmad, R., Yaacob, M. S.

    Published 2007
    “…One of the strategies applied is the modified genetic algorithm which relies on, among other things, the separation of the population into groups where each group undergoes mutual recombination operations. …”
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  12. 12
    Data-driven brain emotional learning-based intelligent controller-PID control of MIMO systems based on a modified safe experimentation dynamics algorithm

    Data-driven brain emotional learning-based intelligent controller-PID control of MIMO systems based on a modified safe experimentation dynamics algorithm by Shahrizal, Saat, Mohd Ashraf, Ahmad, Mohd Riduwan, Ghazali

    Published 2025
    “…The safe experimentation dynamics algorithm (SEDA) is one such method that optimizes controller parameters using data-driven techniques. …”
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  13. 13
    Data-driven brain emotional learning-based intelligent controller-PID control of MIMO systems based on a modified safe experimentation dynamics algorithm

    Data-driven brain emotional learning-based intelligent controller-PID control of MIMO systems based on a modified safe experimentation dynamics algorithm by Shahrizal, Saat, Mohd Ashraf, Ahmad, Mohd Riduwan, Ghazali

    Published 2025
    “…The safe experimentation dynamics algorithm (SEDA) is one such method that optimizes controller parameters using data-driven techniques. …”
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  14. 14
    Efficiency improvement of a standalone photovoltaic system using fuzzy-based maximum power point tracking algorithm

    Efficiency improvement of a standalone photovoltaic system using fuzzy-based maximum power point tracking algorithm by Alhamdawee, Ehsan Mohsin Obaid

    Published 2016
    “…MPPT algorithms can be categorized into classical methods and artificial intelligence-based methods. …”
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  15. 15
    PID controller adjustment for MA-LFC by using imperialist competitive algorithm

    PID controller adjustment for MA-LFC by using imperialist competitive algorithm by Soheilirad, Mohammadsoroush, Farzan, Payam, Othman, Mohammad Lutfi, Karami, K., Hojabri, Mojgan

    Published 2013
    “…In this paper a new evolutionary computing method based on Imperialist Competitive Algorithm (ICA) is used for tuning the elements of a PID controller which is applied in a Multi Area Load Frequency Control System (MA-LFC). …”
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  16. 16
    Improved genetic algorithm for direct current motor high speed controller implemented on field programmable gate array

    Improved genetic algorithm for direct current motor high speed controller implemented on field programmable gate array by Alkhafaji, Falih Salih

    Published 2019
    “…There are many researches have been done to optimize PI controller based evolutionary algorithm, such as Genetic Algorithm (GA). …”
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  17. 17
    Hybrid meta-heuristic algorithm for solving multi-objective aggregate production planning in fuzzy environment

    Hybrid meta-heuristic algorithm for solving multi-objective aggregate production planning in fuzzy environment by Kalaf, Kalaf, Bayda Atiya

    Published 2017
    “…During the course of the present work, two fuzzy methods (modified Zimmermanns approach and modified angelovs approach ) and fourmeta-heuristics and hybrid meta heuristics including; simulated annealing (SA), modified simulated annealing (MSA), hybrid modified simulated annealing and simplex downhill (MSASD), hybrid modified simulated annealing and modified particle swarm optimization (MSAPSO) were proposed. …”
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  18. 18
    Optimum grouping in a modified genetic algorithm for discrete-time, non-linear system identification

    Optimum grouping in a modified genetic algorithm for discrete-time, non-linear system identification by Abd Samad, Md Fahmi

    Published 2007
    “…One of the strategies applied is the modified genetic algorithm which relies on, among other things, the separation of the population into groups where each group undergoes mutual recombination operations. …”
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  19. 19
    Optimization of chemotherapy using metaheuristic optimization algorithms / Prakas Gopal Samy

    Optimization of chemotherapy using metaheuristic optimization algorithms / Prakas Gopal Samy by Prakas Gopal , Samy

    Published 2024
    “…The realization of this objective is steered by two distinct methodologies: the Method for Pure Multi-Objective Optimal Control (PMM) and the Hybrid Method (HM). …”
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  20. 20
    INTELLIGENT OPTIMIZATION OF INTERLINE POWER FLOW CONTROLLER IN TRANSMISSION SYSTEM

    INTELLIGENT OPTIMIZATION OF INTERLINE POWER FLOW CONTROLLER IN TRANSMISSION SYSTEM by MOHAMED ABDELGADIR, KHALID HAROUN

    Published 2010
    “…The optimal parameters are derived to minimize the transmission line losses using three intelligent optimization techniques, namely Particle Swarm Optimization (PSO), Genetic Algorithm (GA) and Simulated Annealing (SA). …”
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