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  • Open Access

    ARTICLE

    Takagi–Sugeno Fuzzy Modeling and Control for Effective Robotic Manipulator Motion

    Izzat Al-Darraji1,2, Ayad A. Kakei2, Ayad Ghany Ismaeel3, Georgios Tsaramirsis4, Fazal Qudus Khan5, Princy Randhawa6, Muath Alrammal4, Sadeeq Jan7,*

    CMC-Computers, Materials & Continua, Vol.71, No.1, pp. 1011-1024, 2022, DOI:10.32604/cmc.2022.022451

    Abstract Robotic manipulators are widely used in applications that require fast and precise motion. Such devices, however, are prompt to nonlinear control issues due to the flexibility in joints and the friction in the motors within the dynamics of their rigid part. To address these issues, the Linear Matrix Inequalities (LMIs) and Parallel Distributed Compensation (PDC) approaches are implemented in the Takagy–Sugeno Fuzzy Model (T-SFM). We propose the following methodology; initially, the state space equations of the nonlinear manipulator model are derived. Next, a Takagy–Sugeno Fuzzy Model (T-SFM) technique is used for linearizing the state space equations of the nonlinear manipulator.… More >

  • Open Access

    ARTICLE

    Fuzzy Based Latent Dirichlet Allocation for Intrusion Detection in Cloud Using ML

    S. Ranjithkumar1,*, S. Chenthur Pandian2

    CMC-Computers, Materials & Continua, Vol.70, No.3, pp. 4261-4277, 2022, DOI:10.32604/cmc.2022.019031

    Abstract The growth of cloud in modern technology is drastic by provisioning services to various industries where data security is considered to be common issue that influences the intrusion detection system (IDS). IDS are considered as an essential factor to fulfill security requirements. Recently, there are diverse Machine Learning (ML) approaches that are used for modeling effectual IDS. Most IDS are based on ML techniques and categorized as supervised and unsupervised. However, IDS with supervised learning is based on labeled data. This is considered as a common drawback and it fails to identify the attack patterns. Similarly, unsupervised learning fails to… More >

  • Open Access

    ARTICLE

    QoS Based Cloud Security Evaluation Using Neuro Fuzzy Model

    Nadia Tabassum1, Tahir Alyas2, Muhammad Hamid3,*, Muhammad Saleem4, Saadia Malik5, Syeda Binish Zahra2

    CMC-Computers, Materials & Continua, Vol.70, No.1, pp. 1127-1140, 2022, DOI:10.32604/cmc.2022.019760

    Abstract Cloud systems are tools and software for cloud computing that are deployed on the Internet or a cloud computing network, and users can use them at any time. After assessing and choosing cloud providers, however, customers confront the variety and difficulty of quality of service (QoS). To increase customer retention and engagement success rates, it is critical to research and develops an accurate and objective evaluation model. Cloud is the emerging environment for distributed services at various layers. Due to the benefits of this environment, globally cloud is being taken as a standard environment for individuals as well as for… More >

  • Open Access

    ARTICLE

    Predictive Control Algorithm for Urban Rail Train Brake Control System Based on T-S Fuzzy Model

    Xiaokan Wang1, 2, *, Qiong Wang2, Shuang Liang3

    CMC-Computers, Materials & Continua, Vol.64, No.3, pp. 1859-1867, 2020, DOI:10.32604/cmc.2020.011032

    Abstract Urban rail transit has the advantages of large traffic capacity, high punctuality and zero congestion, and it plays an increasingly important role in modern urban life. Braking system is an important system of urban rail train, which directly affects the performance and safety of train operation and impacts passenger comfort. The braking performance of urban rail trains is directly related to the improvement of train speed and transportation capacity. Also, urban rail transit has the characteristics of high speed, short station distance, frequent starting, and frequent braking. This makes the braking control system constitute a time-varying, time-delaying and nonlinear control… More >

  • Open Access

    ARTICLE

    Synthesized AI LMI-based Criterion for Mechanical Systems

    Jcy Chen1,*, Wc Chen1, Tim Chen1, Alex Wilson2, N. Fadilah Jamaludin3, Nertrand Kapron1, Tim Chen4,5, John Burno5

    Sound & Vibration, Vol.53, No.6, pp. 245-250, 2019, DOI:10.32604/sv.2019.04233

    Abstract This paper proposes a novel artificial intelligence sythethized controller in the mechanical system which has high speed computation because of the LMI type criterion. The proposed membership functions are adopted and stabilization criterion of the closed-loop T-S fuzzy systems are obtained through a new parametrized LMI (linear matrix) inequality which is rearranged by machine learning membership functions. More >

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