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  1. 1
    Design and Implementation of Intelligent Interoperability Framework for Heterogeneous Subsystems in Smart Home Environment

    Design and Implementation of Intelligent Interoperability Framework for Heterogeneous Subsystems in Smart Home Environment by Perumal, Thinagaran

    Published 2011
    “…The third algorithm, named as Pro-Active Intelligence algorithm has inspired autonomous action triggering for each event interoperation, using a control action statement that is generated by SOAP packets required for joint execution of tasks among heterogeneous subsystems. …”
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  2. 2
    A real-time integrated fire detection and alarm (FDA) system for network based building automation

    A real-time integrated fire detection and alarm (FDA) system for network based building automation by Anwar, Farhat, Islam, Rounakul, Hussain, Sabahat, Rashid, Muhammad Mahbubur, Shaikh, Zuhaib

    Published 2017
    “…Objectives: An integrated Fire Detection and Alarm (FDA) systems with building automation was studied, to reduce cost and improve their reliability by preventing false alarm, signal drop and network breakdown. This work proposes an improved framework for FDA system to ensure a robust, intelligent network of FDA control panels in real-time. …”
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  3. 3
    Energy Management Strategies for Optimal Hybrid Microgrid Configuration in the Smart Village Context

    Energy Management Strategies for Optimal Hybrid Microgrid Configuration in the Smart Village Context by Fakhar, Adila

    Published 2018
    “…A part of the developed algorithm is used to deal with the optimal scheduling control while the other actuates the dynamic demand response based PV power forecasting. …”
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  4. 4
    Active intelligent control of vibration of flexible plate structures

    Active intelligent control of vibration of flexible plate structures by Md Salleh, Salihatun

    Published 2011
    “…In this work active intelligent control comprises a set of control techniques based on particle swarm optimisation (PSO), real coded genetic algorithm (RCGA) and artificial immune system (AIS). …”
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  5. 5
    Decentralized Intelligent PID based controller tuned by Evolutionary Algorithm for Double Link Flexible Robotic Manipulator with Experimental Validation

    Decentralized Intelligent PID based controller tuned by Evolutionary Algorithm for Double Link Flexible Robotic Manipulator with Experimental Validation by Annisa, Jamali, Mat Darus, I.Z., M. H., Hassan, Tokhi, M.O.

    Published 2018
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  6. 6
    An Intelligent Voltage Controller for a PV Inverter System Using Simulated Annealing Algorithm-Based PI Tuning Approach

    An Intelligent Voltage Controller for a PV Inverter System Using Simulated Annealing Algorithm-Based PI Tuning Approach by Najeeb, Mushtaq, Muhamad, Mansor, Ramdan, Razali, Hamdan, Daniyal, Ali, Mahmood

    Published 2017
    “…This study associates an intelligent voltage controller based PI approach for PV electrical inverter by employing a meta-heuristic optimization algorithmic called a Simulated Annealing (SA) algorithm. …”
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  7. 7
    Modeling and Simulation of Swarm Intelligence Algorithms for Parameters Tuning of PID Controller in Industrial Couple Tank System

    Modeling and Simulation of Swarm Intelligence Algorithms for Parameters Tuning of PID Controller in Industrial Couple Tank System by Ismail, Mohd Khairuddin, Amira Sarayati, Ahmad Dahalan, Amar Faiz, Zainal Abidin, Yee, Yang Lai, Nur Anis, Nordin, Siti Fatimah, Sulaiman, Hazriq Izzuan, Jaafar, Syahrul Hisham, Mohamad, Noor Hafizah, Amer

    Published 2014
    “…This paper explores the applications of two swarm intelligence algorithms in optimizing the PID controller parameters. …”
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  8. 8
    Modeling and Simulation of Swarm Intelligence Algorithms for Parameters Tuning Of PID Controller in Industrial Couple Tank System

    Modeling and Simulation of Swarm Intelligence Algorithms for Parameters Tuning Of PID Controller in Industrial Couple Tank System by Mohd Khairuddin, Ismail, Ahmad Dahalan, Amira Sarayati, Zainal Abidin, Amar Faiz, Yee, Yang Lai, Nordin, Nur Anis, Siti Fatimah, Sulaiman, Jaafar, Hazriq Izzuan, Mohamad, Syahrul Hisham, Amer, Noor Hafizah

    Published 2014
    “…This paper explores the applications of two swarm intelligence algorithms in optimizing the PID controller parameters. …”
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  9. 9
    Developing an intelligent system to acquire meeting knowledge in problem-based learning environments

    Developing an intelligent system to acquire meeting knowledge in problem-based learning environments by Chiang, A., Baba, M.S.

    Published 2006
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  10. 10
    An implementation of brain emotional learning based intelligent controller for AVR system

    An implementation of brain emotional learning based intelligent controller for AVR system by Saat, Shahrizal, Ghazali, Mohd Riduwan, Ahmad, Mohd Ashraf, Mustapha, Nik Mohd Zaitul Akmal, Tumari, Mohd Zaidi Mohd

    Published 2023
    “…In this paper, an intelligent controller based on brain emotional learning called BELBIC is applied and optimized by Particle Swarm optimization algorithm. …”
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  11. 11
    An Intelligent Active Force Control Algorithm to Control an Upper Extremity Exoskeleton for Motor Recovery

    An Intelligent Active Force Control Algorithm to Control an Upper Extremity Exoskeleton for Motor Recovery by Wan Hasbullah, Mohd Isa, Zahari, Taha, Ismail, Mohd Khairuddin, Anwar, P. P. A. Majeed, Khairul Fikri, Muhammad, Ali, Mohammed A. H., Jamaluddin, Mahmud, Zulkifli, Mohamed

    Published 2016
    “…This paper presents the modelling and control of a two degree of freedom upper extremity exoskeleton by means of an intelligent active force control (AFC) mechanism. …”
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  12. 12
    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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  13. 13
    Intelligent PID Controller Tuned by Bacterial Foraging Optimization Algorithm for Vibration Suppression of Horizontal Flexible Structure

    Intelligent PID Controller Tuned by Bacterial Foraging Optimization Algorithm for Vibration Suppression of Horizontal Flexible Structure by Aizat Ikmal, Abd Raof, Muhamad Sukri, Hadi, Intan Zaurah, Mat Darus, Annisa, Jamali, Mat Hussin, Ab Talib, Hanim, Mohd Yatim

    Published 2022
    “…To overcome this drawback, this project developed an intelligent vibration controller based on Bacterial Foraging Optimization (BFO) and incorporated into a Proportional-Integral-Derivative (PID) controller. …”
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  14. 14
    Power system stabilization based on artificial intelligent techniques: a review

    Power system stabilization based on artificial intelligent techniques: a review by Hassan, L.H., Moghavvemi, M., Mohamed, H.A.F.

    Published 2009
    “…Research showed controllers designed based on a conventional control theory, modern and adaptive control theories, suffer from some limitations. …”
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  15. 15
    A fuzzy-active force based control architecture for characterizing a nonlinear MIMO system / Tengku Luqman Tengku Mohamed

    A fuzzy-active force based control architecture for characterizing a nonlinear MIMO system / Tengku Luqman Tengku Mohamed by Tengku Mohamed, Tengku Luqman

    Published 2016
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  16. 16
    An implementation of brain emotional learning based intelligent Controller for AVR system

    An implementation of brain emotional learning based intelligent Controller for AVR system by Shahrizal, Saat, Mohd Riduwan, Ghazali, Mohd Ashraf, Ahmad, Nik Mohd Zaitul Akmal, Mustapha, Mohd Zaidi, Mohd Tumari

    Published 2023
    “…In this paper, an intelligent controller based on brain emotional learning called BELBIC is applied and optimized by Particle Swarm optimization algorithm. …”
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  17. 17
    DESIGN AND ANALYSIS OF BRAIN EMOTIONAL LEARNING BASED INTELLIGENT CONTROLLER (BELBIC) FOR TEMPERATURE CONTROL

    DESIGN AND ANALYSIS OF BRAIN EMOTIONAL LEARNING BASED INTELLIGENT CONTROLLER (BELBIC) FOR TEMPERATURE CONTROL by Siti Rasyidah binti Syed Rabi'i, Siti Rasyidah

    Published 2010
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    Final Year Project
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  18. 18
    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 adjustment improves the balance between exploration and exploitation phases, which enhances control accuracy. The MSEDA was used to tune the brain emotional learning-based intelligent controller (BELBIC) together with a proportional-integral-derivative (PID) controller. …”
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  19. 19
    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 adjustment improves the balance between exploration and exploitation phases, which enhances control accuracy. The MSEDA was used to tune the brain emotional learning-based intelligent controller (BELBIC) together with a proportional-integral-derivative (PID) controller. …”
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  20. 20
    Coordination of PSS and PID controller for power system stability enhancement - overview

    Coordination of PSS and PID controller for power system stability enhancement - overview by Kasilingam G., Pasupuleti J.

    Published 2023
    “…Research showed the design of controllers based on conventional methods; soft computing and population based algorithms suffer from limitations. …”
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