Transactions on Machine Intelligence2821-16935320220901Type 2 Neuro-Fuzzy Controller for a Class of Delayed Nonlinear Systems13915120921710.47176/TMI.2022.139ENK.SabahiAssistant Professor, Department of Engineering Sciences, Faculty of New Technologies, University of Mohaghegh Ardabili, Namin, Iran0000-0002-9571-2208Journal Article20220503This article explores the design of a type 2 neuro-fuzzy controller specifically for managing delayed nonlinear systems through feedback error training. The feedback error training framework incorporates a traditional controller in the feedback loop to stabilize the system. Meanwhile, the forward loop employs a type 2 neuro-fuzzy controller, which serves as an intelligent controller to address system nonlinearity and time delay issues. The parameters of the type 2 neuro-fuzzy controller are fine-tuned using the gradient descent method within this framework. To assess the stability of both the closed-loop system and the parameter adjustment algorithm, a Lyapunov-Krasowski function is utilized. This function demonstrates that the tracking error can be reduced to zero, even with the presence of delay in the control system input. Furthermore, the regulation rules for the intelligent controller's parameters can be derived without needing the exact mathematical model or parameters of the system being controlled, thus simplifying the calculations. The proposed method has been applied to control an inverse pendulum system characterized by nonlinear behavior and time-varying delays in its input due to network-based control. Additionally, sensor measurements are assumed to be noisy. Simulation results validate the effectiveness of the designed controller across various time delay scenarios and noise levels.https://www.tmachineintelligence.ir/article_209217_f041e644b0cdfe0150f99df27fb27e5c.pdfTransactions on Machine Intelligence2821-16935320220901Mutual Coupling Reduction in Cylindrical Microstrip Array Antenna using DGS15215920921810.47176/TMI.2022.152ENA.MonajatiYadegar-e-Imam Khomeini (RAH) Shahre Rey Branch, Islamic Azad University, Tehran, IranN.SafaverdiDepartment of Electrical Engineering, Yadegar-emam Khomeini branch, Islamic Azad University, Tehran, IranJournal Article20220504This study presents the design and analysis of a three-element cylindrical conformal microstrip patch array antenna that exploits the inherent advantages of cylindrical geometries benefits that are often unattainable with traditional planar antenna configurations. Each array element consists of a rectangular microstrip patch excited by a microstrip line, specifically optimized to resonate at a frequency of 5.3 GHz. A central feature of the proposed design is the integration of a dumbbell-shaped Defected Ground Structure (DGS), strategically employed to suppress mutual coupling effects between the adjacent antenna elements. The inclusion of the DGS structure leads to a notable reduction in mutual coupling measured to be approximately 15 dB without compromising the integrity of the radiation characteristics in both the E-plane and H-plane. Comprehensive simulations of the surface wave distribution further confirm the role of the DGS in diminishing surface wave propagation, thereby enhancing the isolation between elements. Beyond its electromagnetic performance, the antenna design offers several practical advantages, including ease of fabrication, mechanical flexibility, and a compact, low-profile form factor that makes it suitable for integration into conformal platforms such as aircraft fuselages or wearable systems. The results indicate that the proposed antenna structure not only achieves efficient inter-element isolation but also maintains desirable radiation properties, marking it as a promising candidate for modern wireless and radar communication applications requiring compact, conformal, and high-performance antenna arrays.https://www.tmachineintelligence.ir/article_209218_b3c4022f1d93d73efac4cb5450e9b1c7.pdfTransactions on Machine Intelligence2821-16935320220901Optimizing Mobile Sink Movement Using Bee Algorithm in Wireless Sensor Networks16017320921910.47176/TMI.2022.160ENG.PoyamehrDepartment of Computer Engineering, Faculty of Electrical and Computer Engineering, Technical and Vocational University, Tehran, IranM.FazeliAssociate Professor, School of Information Technology, Halmstad University, Halmstad, Sweden0000-0002-2874-6256S.MoghaddasiDepartment of Computer Engineering, Faculty of Engineering, Borujerd Branch, Islamic Azad University, Borujerd, IranJournal Article20220303Wireless Sensor Networks (WSNs) consist of a large number of spatially distributed wireless sensor nodes that monitor and collect environmental data, subsequently transmitting it to a central base station for processing and analysis. Efficient and energy-aware data collection remains a critical challenge in WSNs due to the limited power resources of individual sensor nodes. One widely adopted strategy involves the use of a sink node to aggregate data from across the network. Recently, mobile sink approaches have gained significant attention for their potential to reduce energy consumption and improve data collection efficiency. In this thesis, a novel routing strategy is proposed that leverages the Artificial Bee Colony (ABC) algorithm for managing the trajectory and data aggregation process of a mobile sink. The ABC algorithm, inspired by the foraging behavior of honeybees, is applied to dynamically optimize the path of the mobile sink, minimizing communication overhead and balancing energy usage across the network. The proposed approach is designed to reduce the latency in data acquisition and prolong the overall lifetime of the network. Comprehensive simulation experiments were conducted to evaluate the performance of the proposed method against conventional techniques. The results demonstrate that the ABC-based routing method significantly reduces energy consumption and minimizes data reading delays. Consequently, it contributes to enhanced quality of service (QoS) and greater sustainability of the wireless sensor network infrastructure.https://www.tmachineintelligence.ir/article_209219_bcfc06227ae641791bd26076cc52cb06.pdfTransactions on Machine Intelligence2821-16935320220901Design of a Supplementary Controller for STATCOM and Real-Time Parameter Estimation Using Neural Networks in a Hybrid Wind Farm Connected to the Grid17419521462310.47176/TMI.2022.174ENZ.GhadimiMaster's student, Department of Electrical Engineering, University of Guilan, Rasht, IranA.KaramiAssociate Professor, Department of Electrical Engineering, University of Guilan, Rasht, IranJournal Article20220604In recent years, power systems have encountered numerous challenges, particularly with the growing integration of renewable energy sources. Among these, wind energy has emerged as a clean and cost-effective option, but its impact on power system stability has become a critical concern. This impact largely depends on the type of induction generators used in wind turbines, which are primarily categorized into two types: fixed-speed wind turbines, which typically use squirrel cage induction generators (SCIG), and variable-speed wind turbines, which rely on doubly-fed induction generators (DFIG). A combined wind farm (CWF) leverages the advantages of both generator types. To enhance the dynamic performance of such a wind farm, the integration of compensators is essential. Among these, the Static Synchronous Compensator (STATCOM), a third-generation FACTS (Flexible AC Transmission Systems) device, has gained considerable attention for its effectiveness. In this study, a power system connected to a combined wind farm is designed, with a STATCOM installed at one of its buses. To further improve the damping of system oscillations during faults, a supplementary PID controller is incorporated into the STATCOM structure. The Particle Swarm Optimization (PSO) algorithm is employed to determine the optimal PID controller coefficients. However, as the PSO process can be computationally intensive, an Artificial Neural Network (ANN) is introduced to estimate the PID parameters in real time when system operating conditions change. Simulation results, conducted using MATLAB/Simulink software, demonstrate the effectiveness of the proposed approach, validating its potential to enhance power system stability in the presence of combined wind farms.https://www.tmachineintelligence.ir/article_214623_1d3f19ecde02f330348a6d45bc0f8bab.pdfTransactions on Machine Intelligence2821-16935320220901Performance Analysis and Energy Conversion of Control’s Solar-Geothermal Combined Cooling, Heating and Power (CCHP) Systems with Hydrogen Production19620923594310.47176/TMI.2022.196ENM.A.Allahrabbi ShiraziDepartment of Energy and Aerospace Engineering, Shiraz University, Shiraz, IranGH.Yeganeh FardDepartment of Mechanical Engineering, Alzahra University, Tehran ،IranN.ZadsarDepartment of Mechanical Engineering, Alzahra University, Tehran ،IranJournal Article20220512This study employs the Response Surface Method (RSM) and transient analysis to optimize the design of a solar-assisted-geothermal combined cooling, heating, and power (SG-CCHP) system, integrated with hydrogen storage, for residential applications. The optimization focuses on both energy efficiency and economic performance. The SG-CCHP system comprises two steam turbines (STs), photovoltaic/thermal (PV/T) collectors, a fuel cell circuit, an absorption chiller, a heat pump (HP), and energy storage systems, including battery cells and a hydrogen storage unit. System performance is evaluated through transient analysis using the TRNSYS modeling tool. Key design parameters are identified, and the Design of Experiments (DOE) method is utilized to determine their optimal configuration. Multiple simulation scenarios are generated using DOE, and RSM is applied to analyze the results. Once the optimal SG-CCHP configuration is identified, the transient interactions between control design factors and techno-economic metrics are examined. The findings reveal that the optimized system achieves significant reductions in annual life cycle costs, thermal comfort levels, total energy consumption, and natural gas usage by the auxiliary boiler. Furthermore, the integration of battery and hydrogen storage components enhances system efficiency, with the electrolyzer, fuel cell, PV/T thermal, and electrical systems reaching annual efficiencies of 90%, 60%, 23%, and 18%, respectively. These results demonstrate the potential of the optimized SG-CCHP system to improve both energy performance and economic viability in residential settings.https://www.tmachineintelligence.ir/article_235943_8c51c84090a0e6033ca7fc0314401dea.pdfTransactions on Machine Intelligence2821-16935320220901Effect of Grading Index on The Stress Response of a Rotating FGM Hollow Cylinder with Functionally Graded Piezoelectric Layers21022121462610.47176/TMI.2022.210ENM.SaadatfarAssociate Prof. of Mechanical Engineering, Department of Mechanical Engineering, University of Qom, Qom, IranY.Bik IravaniMSc. Student of Mechanical Engineering Department of Mechanical Engineering, University of Qom, Qom, IranW.T.SalehMSc. Student of Mechanical Engineering Department of Mechanical Engineering, University of Qom, Qom, IranI. K. I.Al-hamadaniMSc. Student of Mechanical Engineering Department of Mechanical Engineering, University of Qom, Qom, IranK.H.AyishMSc. Student of Mechanical Engineering Department of Mechanical Engineering, University of Qom, Qom, IranJournal Article20220610This study presents a comprehensive analytical investigation into the thermo-electro-elastic response of a rotating long hollow cylinder composed of a functionally graded material (FGM), with radially polarized functionally graded piezoelectric material (FGPM) layers perfectly bonded to its inner and outer surfaces. The cylinder is subjected to simultaneous thermal, electrical, and mechanical loadings, providing a realistic simulation of operational conditions in advanced electromechanical systems. The material properties of both the FGM cylinder and the FGPM layers are assumed to vary continuously along the radial direction according to a power-law distribution, while Poisson’s ratio remains constant in the FGM region. The structure is analyzed under steady-state conditions while rotating at a constant angular velocity around its central axis. Closed-form analytical expressions are derived for the radial displacement, stress components, and electric potential using the theory of elasticity and electro-mechanics. The results are validated through parametric studies that explore the effects of key variables such as the material gradation index, angular velocity, thickness ratio, applied electrical voltage, and boundary temperatures. Numerical simulations illustrate how these parameters influence the stress distribution and overall structural behavior. The findings offer valuable design insights for advanced smart structures and rotating piezoelectric devices, emphasizing the importance of functional grading in enhancing mechanical integrity and electromechanical coupling performance under complex operational environments.https://www.tmachineintelligence.ir/article_214626_a32a4ebfafa97ee04a462402078ab595.pdf