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  • Open Access

    ARTICLE

    Deep Learning Anomaly Detection Based on Hierarchical Status-Connection Features in Networked Control Systems

    Jianming Zhao1,2,3,4, Peng Zeng1,2,3,4,*, Chunyu Chen1,2,3,4, Zhiwei Dong5, Jongho Han6

    Intelligent Automation & Soft Computing, Vol.30, No.1, pp. 337-350, 2021, DOI:10.32604/iasc.2021.016966

    Abstract As networked control systems continue to be widely used in large-scale industrial productions, industrial cyber-attacks have become an inevitable problem that can cause serious damage to critical infrastructures. In practice, industrial intrusion detection has been widely acknowledged to detect abnormal communication behaviors. However, unlike traditional IT systems, networked control systems have their own communication characteristics due to specific industrial communication protocols. Thus, simple cyber-attack modeling is inadequate and impractical for high-efficiency intrusion detection because the characteristics of network control systems are less considered. Based on the status information and transmission connection in industrial communication data payloads, which can properly express… More >

  • Open Access

    ARTICLE

    A Deep Learning Approach for the Mobile-Robot Motion Control System

    Rihem Farkh1,4,*, Khaled Al jaloud1, Saad Alhuwaimel2, Mohammad Tabrez Quasim3, Moufida Ksouri4

    Intelligent Automation & Soft Computing, Vol.29, No.2, pp. 423-435, 2021, DOI:10.32604/iasc.2021.016219

    Abstract A line follower robot is an autonomous intelligent system that can detect and follow a line drawn on floor. Line follower robots need to adapt accurately, quickly, efficiently, and inexpensively to changing operating conditions. This study proposes a deep learning controller for line follower mobile robots using complex decision-making strategies. An Arduino embedded platform is used to implement the controller. A multilayered feedforward network with a backpropagation training algorithm is employed. The network is trained offline using Keras and implemented on a ATmega32 microcontroller. The experimental results show that it has a good control effect and can extend its application. More >

  • Open Access

    ARTICLE

    Position Sensorless Control System of Permanent Magnet Synchronous Linear Motor Based on Sliding Mode Observer with an Improved Phase-Locked Loop

    Jin Zhang1, Youliang Tang1, Feng Yu2,*

    Energy Engineering, Vol.118, No.4, pp. 1083-1094, 2021, DOI:10.32604/EE.2021.014482

    Abstract In this paper, position sensorless control system of permanent magnet synchronous linear motor (PMSLM) based on sliding mode observer (SMO) with an improved phase-locked loop (PLL) is studied. Firstly, according to the mathematical model, a SMO is designed for sensorless control PMSLM drive. Thereafter, an improved PLL is proposed to tackle the imperfection of data overflow existed in the traditional PLL. The designed SMO incorporating with the improved PLL can be effectively suppress the pulsation of the estimated position and hence the chattering of the derived electrical angular velocity. At last, simulated and experimental results are presented to verify the… More >

  • Open Access

    ARTICLE

    Intelligent Autonomous-Robot Control for Medical Applications

    Rihem Farkh1,2, Haykel Marouani1,*, Khaled Al Jaloud1, Saad Alhuwaimel3, Mohammad Tabrez Quasim4, Yasser Fouad1

    CMC-Computers, Materials & Continua, Vol.68, No.2, pp. 2189-2203, 2021, DOI:10.32604/cmc.2021.015906

    Abstract The COVID-19 pandemic has shown that there is a lack of healthcare facilities to cope with a pandemic. This has also underscored the immediate need to rapidly develop hospitals capable of dealing with infectious patients and to rapidly change in supply lines to manufacture the prescription goods (including medicines) that is needed to prevent infection and treatment for infected patients. The COVID-19 has shown the utility of intelligent autonomous robots that assist human efforts to combat a pandemic. The artificial intelligence based on neural networks and deep learning can help to fight COVID-19 in many ways, particularly in the control… More >

  • Open Access

    ARTICLE

    An Anomaly Detection Method of Industrial Data Based on Stacking Integration

    Kunkun Wang1,2, Xianda Liu2,3,4,*

    Journal on Artificial Intelligence, Vol.3, No.1, pp. 9-19, 2021, DOI:10.32604/jai.2021.016706

    Abstract With the development of Internet technology, the computing power of data has increased, and the development of machine learning has become faster and faster. In the industrial production of industrial control systems, quality inspection and safety production of process products have always been our concern. Aiming at the low accuracy of anomaly detection in process data in industrial control system, this paper proposes an anomaly detection method based on stacking integration using the machine learning algorithm. Data are collected from the industrial site and processed by feature engineering. Principal component analysis (PCA) and integrated rule tree method are adopted to… More >

  • Open Access

    ARTICLE

    Anomaly Detection in ICS Datasets with Machine Learning Algorithms

    Sinil Mubarak1, Mohamed Hadi Habaebi1,*, Md Rafiqul Islam1, Farah Diyana Abdul Rahman, Mohammad Tahir2

    Computer Systems Science and Engineering, Vol.37, No.1, pp. 33-46, 2021, DOI:10.32604/csse.2021.014384

    Abstract An Intrusion Detection System (IDS) provides a front-line defense mechanism for the Industrial Control System (ICS) dedicated to keeping the process operations running continuously for 24 hours in a day and 7 days in a week. A well-known ICS is the Supervisory Control and Data Acquisition (SCADA) system. It supervises the physical process from sensor data and performs remote monitoring control and diagnostic functions in critical infrastructures. The ICS cyber threats are growing at an alarming rate on industrial automation applications. Detection techniques with machine learning algorithms on public datasets, suitable for intrusion detection of cyber-attacks in SCADA systems, as… More >

  • Open Access

    ARTICLE

    Flower Pollination Heuristics for Nonlinear Active Noise Control Systems

    Wasim Ullah Khan1,*, Yigang He1, Muhammad Asif Zahoor Raja2, Naveed Ishtiaq Chaudhary3, Zeshan Aslam Khan3, Syed Muslim Shah4

    CMC-Computers, Materials & Continua, Vol.67, No.1, pp. 815-834, 2021, DOI:10.32604/cmc.2021.014674

    Abstract Abstract In this paper, a novel design of the flower pollination algorithm is presented for model identification problems in nonlinear active noise control systems. The recently introduced flower pollination based heuristics is implemented to minimize the mean squared error based merit/cost function representing the scenarios of active noise control system with linear/nonlinear and primary/secondary paths based on the sinusoidal signal, random and complex random signals as noise interferences. The flower pollination heuristics based active noise controllers are formulated through exploitation of nonlinear filtering with Volterra series. The comparative study on statistical observations in terms of accuracy, convergence and complexity measures… More >

  • Open Access

    ARTICLE

    Smart Object Detection and Home Appliances Control System in Smart Cities

    Sulaiman Khan1, Shah Nazir1, Habib Ullah Khan2,*

    CMC-Computers, Materials & Continua, Vol.67, No.1, pp. 895-915, 2021, DOI:10.32604/cmc.2021.013878

    Abstract During the last decade the emergence of Internet of Things (IoT) based applications inspired the world by providing state of the art solutions to many common problems. From traffic management systems to urban cities planning and development, IoT based home monitoring systems, and many other smart applications. Regardless of these facilities, most of these IoT based solutions are data driven and results in small accuracy values for smaller datasets. In order to address this problem, this paper presents deep learning based hybrid approach for the development of an IoT-based intelligent home security and appliance control system in the smart cities.… More >

  • Open Access

    ARTICLE

    Imperfect Premise Matching Controller Design for Interval Type-2 Fuzzy Systems under Network Environments

    Zejian Zhang1, Dawei Wang2,*, Xiao-Zhi Gao3

    Intelligent Automation & Soft Computing, Vol.27, No.1, pp. 173-189, 2021, DOI:10.32604/iasc.2021.012805

    Abstract The interval type-2 fuzzy sets can describe nonlinear plants with uncertain parameters. It exists in nonlinearity. The parameter uncertainties extensively exist in the nonlinear practical Networked Control Systems (NCSs), and it is paramount to investigate the stabilization of the NCSs on account of the section type-2 fuzzy systems. Notice that most of the existing research work is only on account of the convention Parallel Distribution Compensation (PDC). For overcoming the weak point of the PDC and acquire certain guard stability conditions, the state tickling regulator under imperfect premise matching can be constructed to steady the NCSs using the section type-2… More >

  • Open Access

    ARTICLE

    A Formal Testing Model for Operating Room Control System Using Internet of Things

    Moez Krichen1, Seifeddine Mechti2, Roobaea Alroobaea3, Elyes Said4, Parminder Singh5, Osamah Ibrahim Khalaf6, Mehedi Masud3,*

    CMC-Computers, Materials & Continua, Vol.66, No.3, pp. 2997-3011, 2021, DOI:10.32604/cmc.2021.014090

    Abstract Technological advances in recent years have significantly changed the way an operating room works. This work aims to create a platform to solve the problems of operating room occupancy and prepare the rooms with an environment that is favorable for all operations. Using this system, a doctor can control all operation rooms, especially before an operation, and monitor their temperature and humidity to prepare for the operation. Also, in the event of a problem, an alert is sent to the nurse responsible for the room and medical stuff so that the problem can be resolved. The platform is tested using… More >

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