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  1. 1
    Optimization Of Pid Controller Using Grey Wolf Optimzer And Dragonfly Algorithm

    Optimization Of Pid Controller Using Grey Wolf Optimzer And Dragonfly Algorithm by Nik Mohamed Hazli, Nik Muhammad Aiman

    Published 2018
    “…The expected result is the algorithms are able to optimise the PID controller. …”
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  2. 2
    Optimisation of automatic generation control performance in two-area power system with pid controllers using mepso / Lu Li

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

    Published 2018
    “…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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  3. 3
    Optimisation of PID controller for load frequency control in two-area power system using evolutionary particle swarm optimisation

    Optimisation of PID controller for load frequency control in two-area power system using evolutionary particle swarm optimisation by Illias, Hazlee Azil, Zahari, A.F.M., Mokhlis, Hazlie

    Published 2016
    “…Therefore, to overcome this situation, in this work, particle swarm optimization (PSO) and evolutionary particle swarm optimization (EPSO) algorithms were employed in a LFC of twoarea power system to optimise the performance of the PID controller. …”
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  4. 4
    Active vibration control using pole placement method of a flexible plate structure optimised by genetic algorithm

    Active vibration control using pole placement method of a flexible plate structure optimised by genetic algorithm by Tuan Abdul Rahman, Tuan Ahmad Zahidi, Mat Darus, Intan Zaurah

    Published 2012
    “…A second order ARX model optimised by genetic algorithm (GA) is employed to represent the dynamical system and then feedback controller using pole placement method is exploited to stabilise the system and attenuate the disturbance vibration. …”
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  5. 5
    Performance evaluation of PID controller optimisation for wheel mobile robot using Bat based optimisation algorithm

    Performance evaluation of PID controller optimisation for wheel mobile robot using Bat based optimisation algorithm by ,, Dwi Pebrianti, Ann Ayop azmi, Nurnajmi Qasrina, Bayuaji, Luhur, Suarin, Nur Aisyah Syafinaz, ,, Muhammad Syafrullah

    Published 2022
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  6. 6
    Genetic algorithm optimisation for fuzzy control of wheelchair lifting and balancing

    Genetic algorithm optimisation for fuzzy control of wheelchair lifting and balancing by Ahmad, Salmiah, Tokhi, M. Osman, Toha, Siti Fauziah

    Published 2009
    “…General rules of thumb allow heuristic tuning of the parameters but a proper optimisation mechanism will perform better. Genetic Algorithm is used to control the two-wheeled wheelchair and results show that the optimised parameters give better system performance.…”
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  7. 7
    A comparative evaluation of PID-based optimisation controller algorithms for DC motor

    A comparative evaluation of PID-based optimisation controller algorithms for DC motor by Ahamed S.R., Parumasivam P., Hossain Lipu M.S., Hannan M.A., Ker P.J.

    Published 2023
    “…Controllers; DC motors; Electric control equipment; Particle swarm optimization (PSO); Proportional control systems; Three term control systems; Two term control systems; Backtracking search algorithms; Comparative analysis; Comparative evaluations; Controller algorithm; Industrial activities; Optimum parameters; Particle swarm optimisation; Proportional integral derivative controllers; Electric machine control…”
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  8. 8
    A refined differential evolution algorithm for improving the performance of optimization process

    A refined differential evolution algorithm for improving the performance of optimization process by A. R., Yusoff, Nafrizuan, Mat Yahya

    Published 2011
    “…Various Artificial Intelligent (AI) algorithms can be applied in solving optimization problems. …”
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  9. 9
    Novel Metaheuristic Hybrid Spiral-Dynamic Bacteria-Chemotaxis Algorithms for Global Optimisation

    Novel Metaheuristic Hybrid Spiral-Dynamic Bacteria-Chemotaxis Algorithms for Global Optimisation by Ahmad Nor Kasruddin, Nasir, Tokhi, M. O.

    Published 2015
    “…This paper presents hybrid spiral-dynamic bacteria-chemotaxis algorithms for global optimisation and their application to control of a flexible manipulator system. …”
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  10. 10
    Comparison between Lamarckian Evolution and Baldwin Evolution of neural network

    Comparison between Lamarckian Evolution and Baldwin Evolution of neural network by Taha, Imad, Inazy, Qabas

    Published 2006
    “…We presented hybrid genetic algorithm for optimizing weights as well as the topology of artificial neural networks, by introducing the concepts of Lamarckian and Baldwin evolution effects. …”
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  11. 11
    Two level Differential Evolution algorithms for ARMA parameters estimatio

    Two level Differential Evolution algorithms for ARMA parameters estimatio by Salami, Momoh Jimoh Emiyoka, Tijani, Ismaila, Aibinu, Abiodun Musa

    Published 2013
    “…The first level searches for the appropriate model order while the second level computes the optimal/sub-optimal corresponding parameters. The performance of the algorithm is evaluated using both simulated ARMA models and practical rotary motion system. …”
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  12. 12
    Two-wheeled LEGO EV3 Robot stabilisation control using fuzzy logic based PSO algorithm

    Two-wheeled LEGO EV3 Robot stabilisation control using fuzzy logic based PSO algorithm by M. F., Maharuddin, Normaniha, Abdul Ghani, N. F., Jamin

    Published 2019
    “…The result of the fuzzy logic controller without optimisation is compared with the fuzzy logic controller with optimisation. …”
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  13. 13
    Optimised intelligent tilt controller scheme using genetic algorithms

    Optimised intelligent tilt controller scheme using genetic algorithms by Zamzuri, Hairi, Zolotas, Argyrios, Goodall, Roger

    Published 2006
    “…This paper presents work on a fuzzy control design for improving the performance of tilting trains with local-per vehicle control, i.e. without employing precedence control.An optimisation procedure using Genetic Algorithms as employed to determine both the best fuzzy output membership function and best PID controller parameters. …”
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  14. 14
    Hybrid algorithm for NARX network parameters' determination using differential evolution and genetic algorithm

    Hybrid algorithm for NARX network parameters' determination using differential evolution and genetic algorithm by Salami, Momoh Jimoh Eyiomika, Tijani, Ismaila, Isqeel , Abdullateef Ayodele, Aibinu, Abiodun Musa

    Published 2013
    “…A hybrid optimization algorithm using Differential Evolution (DE) and Genetic Algorithm (GA) is proposed in this study to address the problem of network parameters determination associated with the Nonlinear Autoregressive with eXogenous inputs Network (NARX-network). …”
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  15. 15
    An improved leader particle swarm optimisation algorithm for solving flexible ac transmission systems optimisation problem in power system

    An improved leader particle swarm optimisation algorithm for solving flexible ac transmission systems optimisation problem in power system by Jordehi, Ahmad Rezaee

    Published 2014
    “…The results of applying improved leader PSO to IEEE 14 bus power system shows its significant outperformance over six other optimisation algorithms including conventional PSO, mutated PSO, enhanced PSO, harmony search,genetic algorithm and gravitational search algorithm. …”
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  16. 16
    Crossover-first differential evolution for improved global optimization in non-uniform search landscapes

    Crossover-first differential evolution for improved global optimization in non-uniform search landscapes by Teo, Jason Tze Wi, Mohd Hanafi Ahmad Hijazi, Hui, Keng Lau, Salmah Fattah, Aslina Baharum

    Published 2015
    “…The differential evolution (DE) algorithm is currently one of the most widely used evolutionary-based optimizers for global optimization due to its simplicity, robustness and efficiency. …”
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  17. 17
    Reliably optimal PMU placement using disparity evolution-based genetic algorithm

    Reliably optimal PMU placement using disparity evolution-based genetic algorithm by Matsukawa, Yoshiaki, Othman, Mohammad Lutfi, Watanabe, Masayuki, Mitani, Yasunori

    Published 2017
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  18. 18
    Evolvable traffic signal control for intersection congestion alleviation with enhanced particle swarm optimisation

    Evolvable traffic signal control for intersection congestion alleviation with enhanced particle swarm optimisation by Helen Sin Ee Chuo, Min Keng Tan, Alex Chee Hoe Chong, Renee Ka Yin Chin, Kenneth Tze Kin Teo

    Published 2017
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  19. 19
    Differential evolution optimization algorithm based on generation systems reliability assessment integrated with wind energy

    Differential evolution optimization algorithm based on generation systems reliability assessment integrated with wind energy by Kadhem, Athraa Ali, Abdul Wahab, Noor Izzri, Abdalla, Ahmed N.

    Published 2019
    “…This stuffy proposed a novel optimization method labeled the "Differential Evolution Optimization Algorithm" (DEOA) to assess the reliability of power generation systems (PGS). …”
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  20. 20
    Performance comparison of differential evolution and particle swarm optimization in constrained optimization

    Performance comparison of differential evolution and particle swarm optimization in constrained optimization by Iwan, Mahmud, Akmeliawati, Rini, Faisal, Tarig, Al-Assadi, Hayder M.A.A.

    Published 2012
    “…Particle swarm optimization (PSO) and differential evolution (DE) are among the well-known modern optimization algorithms. …”
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