فهرست مطالب

Journal of Majlesi Journal of Mechatronic Systems
Volume:11 Issue: 1, Mar 2022

  • تاریخ انتشار: 1401/04/08
  • تعداد عناوین: 6
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  • Mostafa Eidiani, Mohammad Kargar Pages 1-6

    Traditional energy production, such as production, transmission, and distribution, as well as consumption, has produced a significant disparity between output and consumption. As a result, the manufacturing sector's energy demand rises, as does fossil fuel use, causing economic and environmental concerns. Today, because of worries about the impact of greenhouse gases and global warming on the environment. The electrical sector has evolved toward the use of distributed generation (DG) in the power system, particularly at the distribution network level, as a result of government incentive programs. The inclusion of DG in the electricity system has resulted in several advantages, including reduced transmission line losses, increased system dependability and flexibility, and reduced transmission line and distribution feeder density. Both when linked to the mains and when utilized independently of the mains (islands), they may be coordinated and regulated. Microgrids can employ a variety of renewable energy sources as major energy suppliers, including solar cells (PV), wind turbines, and tiny water. As a result, microgrids can boost the power grid's efficiency and efficacy, as well as provide a solution to the energy problem and global warming.

    Keywords: Microgrids, Distributed Generation, Renewable Energy Sources, System Stability
  • Ali Fayazi, H. Ghayoumi Zadeh, A. Soltani Sangi Pages 7-17

    In this paper‎, ‎an efficient optimized fractional-order fuzzy proportional-integral-derivative controller (FOFPID) based on biogeography-based optimization (BBO) method is designed for automatic generation control of a two-zone four unit hydro-thermal power system. ‎Studies were conducted in two scenarios‎. ‎In the first scenario‎, ‎the simulation was carryout for power system with pure-thermal units and in the second scenario; the simulation was performed for hydro-thermal power system‎. ‎In each scenario‎, ‎Ten percent load changes have occurred in both areas‎. ‎Moreover‎, ‎the simulations were also performed by applying the conventional PI‎, ‎PID‎, ‎and the hybrid PSO-PS based Fuzzy-PI controllers for two aforementioned scenarios‎. The numerical simulation results illustrated that the proposed optimized control scheme outperforms the other controllers such as the conventional PI‎, ‎PID‎, ‎and the hybrid PSO-PS based Fuzzy-PI controllers under uncertainties in terms of minimizing frequency deviations‎. ‎Such that we had a decrease for the Integral Square Time Square Error (ISTSE) and settling time‎, ‎with a 15% and 43% reduction‎, ‎respectively‎. ‎Moreover‎, ‎the simulation results were also demonstrate the effectiveness and the convergence of the BBO algorithm‎.

    Keywords: Automatic Generation Control, Load Frequency Control, Biogeography-Based Optimization Fractional-Order Controller
  • Zargham Heidari, Hamed Gorginpour, Mahdi Shahparasti Pages 19-30

    Distributed computing is a field of the vast computer science that deals with distributed systems. These systems have a significant role in computing with high efficiency. One of the important cases with a great role in distributed systems is ​​the self-stabilizing concept. One of the new algorithms with a critical role in engineering and computer science is self-stabilization algorithm. This algorithm is known as a lightweight and convenient property relative to other classic solutions and methods of fault tolerance in obtaining fault tolerance (FT). Moreover, in terms of time and space, the art of this algorithm is that it needs less time and space. These features have made the self-stabilization algorithm highly promising for use in distributed systems that are equipped with low computing and low memory processes.

    Keywords: Self-stabilization algorithm, FT, convergence, self-stabilizing time, distributed systems
  • Taher Abedinzadeh, Jaber Pouladi, Ali Daghigh Pages 31-35

    The purpose of this paper is to investigate how to maximize the power output of a DFIG based wind turbine. So, an optimization method based on mathematical analysis has been performed in two generators. So, the exact terms of output power and loss as a function of the slip generator, rotor excitation voltage amplitude and phase angle at different wind speeds are derived. The results show that the maximum output power of turbine does not happen at maximum input power (wind turbine mechanical power). The effect of device parameters on the maximum output power has been investigated and it has been shown these parameters have a greater impact on maximum output power in the machines with lower power. The required modeling is performed using MATLAB.

    Keywords: Doubly Fed Induction Generator, optimization of output power, wind turbine
  • Puya Gholian mohamadi, MohammadReza Yousefi, Khoshnam Shojaee Pages 37-46

    Diagnosis of diseases with the help of new methods has received much attention. One of these diseases is amyotrophic lateral sclerosis. In this disease, neurons cause progressive and irreparable damage to the central nervous system (brain and spinal cord) and peripheral nervous system. Symptoms of upper motor neurons as well as symptoms of lower motor neurons are seen. It is possible to diagnose this disease from kinematic dynamics analysis data. Clinical methods in diagnosing this disease face significant errors. Machine learning methods are an effective way to diagnose these diseases. The proposed method of this research consists of five steps. Pre-processing, feature extraction, dimension reduction, classification and evaluation. The novelty of this article is in using classifier in the diagnosis of this disease. In classification fusion, the types of linear and non-linear classifications in a fusion method with each other will diagnose the disease with higher accuracy

    Keywords: Neurodegenerative Diseases, Dynamic Gait Analysis, Classification, Principal Component Analysis, Classification Fusion
  • Amin Eskandari Pages 47-50

    The Hamiltonian cycle problem (HCP) finds a cycle of length N in an N-vertices graph. We consider a graph G with an associated set of matrices. The weight of each arc corresponds to a cell in the matrices. We consider a multi-objective variant of the HCP and compute a Pareto set of solutions that minimize the weights of arcs for each objective. The HCP problem can be solved using an embedded stochastic process using the Branch-and-Fix algorithm. We extend the Branch-and-Fix algorithm to address multi-objective HCPs by computing different Hamiltonian cycles and fathoming the tree branches at earlier stages. With the algorithm, a valid solution can be produced during the execution, which improves the quality of the Pareto Set over time.

    Keywords: Multi-objective optimization, Discrete optimization problems, Hamiltonian cycle problem, Branching algorithm