Search Results - (( simulation optimization modified algorithm ) OR ( control optimization method algorithm ))

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  1. 1

    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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    Thesis
  2. 2

    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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    Article
  3. 3

    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
  4. 4

    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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    Thesis
  5. 5

    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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    Article
  6. 6

    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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    Thesis
  7. 7

    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
    “…The semi-active suspension system outperformed other suspension systems because it contains an intelligent actuator that can give the appropriate force to dissipate unwanted vibration using intelligent and real-time controllers. In this paper, MR fluid damper with Fuzzy-PID controller is examined to be optimized using a modified DE algorithm. …”
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    Article
  8. 8

    Comparison of mabsa, PSO and GWO of PI-PD controller for dc motor by Nur Naajihah, Ab Rahman

    Published 2024
    “…The swarm intelligence group selected Particle Swarm Optimization (PSO), Grey Wolf Optimization (GWO), and Modified Adaptive Bats Sonar Algorithms (MABSA) to optimize the parameters of the PI-PD controller. …”
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    Thesis
  9. 9

    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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    Final Year Project
  10. 10

    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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    Thesis
  11. 11

    Optimisation of automatic generation control performance in two-area power system with pid controllers using mepso / Lu Li by Lu , Li

    Published 2018
    “…The AGC in two-area power system was constructed and simulated by using MATLAB R2017b software. From the simulation results, it was found that with the same number of PID controllers, the performance of AGC optimised by using MEPSO-TVAC algorithm is better in terms of overshoot and fitness value than using EPSO and PSO algorithms. …”
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    Thesis
  12. 12

    Intelligent Optimization Techniques for Optimal Power Flow using Interline Power Flow Controller by Mohamed, Mohamed, K.H, Kondapalli, Rama Rao. K. S.

    Published 2010
    “…The optimal control parameters are derived to minimize the transmission line losses employing three intelligent optimization techniques, namely Particle Swarm Optimization (PSO), Genetic Algorithm and Simulated Annealing. …”
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    Conference or Workshop Item
  13. 13

    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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    Thesis
  14. 14

    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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    Thesis
  15. 15

    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
    “…The genetic algorithm approach is widely recognized as an effective and flexible optimization method for system identification. …”
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    Article
  16. 16

    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
    “…he genetic algorithm approach is widely recognized as an effective and flexible optimization method for system identification. …”
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    Article
  17. 17

    Solving the integrated inventory supply chain problems using meta-heuristic methods / Seyed Mohsen Mousavi by Seyed Mohsen , Mousavi

    Published 2018
    “…A Modified Particle Swarm Optimization (MPSO) algorithm, a Genetic Algorithm (GA), a modified fruit fly optimization algorithm (MFOA) and a simulated annealing (SA) algorithm were used to find the optimal solution. …”
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    Thesis
  18. 18

    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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    Conference or Workshop Item
  19. 19

    Power quality improvement in distribution systems considering Optimum D-STATCOM placement by Farhoodnea, Masoud, Azah Mohamed, Hussain Shareef, Zayandehroodi, Hadi

    Published 2013
    “…The obtained results are compared with the particle swarm optimization and the genetic algorithm. The simulation and comparison results verify the ability of the FA to accurately determine the optimal location and size of the D-STATCOM in radial distribution systems.…”
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    Article
  20. 20

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

    Published 2007
    “…The genetic algorithm approach is widely recognized as an effective and flexible optimization method for system identification. …”
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    Article