@article{ author = {Khatibinia, Meissam and Gharaveisi, Ali Akbar}, title = {Design of fuzzy Controller Using Genetic Multiple Attributed Decision Making for Automatic Voltage Regulator System}, abstract ={Controller design and optimization can be done with multiobjective approach, in the other hand, controller design and optimization problem is a multiobjective or multiple attributed problem. In this paper, an optimal method is presented and called genetic multiple attributed decision making (GMADM). This method is has two properties it is a multiobjective method and it try to find a set of appropriate optimal solutions. After presenting the method, a fuzzy controller is designed and optimized by GMADM method. This optimal controller is applied on a nonlinear automatic voltage regulator system (AVR). The studied system is the main part of generator, because, the output voltage level is kept constant by AVR system. The simulation results show that the propose method acts well and it is efficient.}, Keywords = {Genetic multiple attributed decision making, Entropy, TOPSIS, Pareto, Automatic voltage regulator system.}, volume = {7}, Number = {4}, pages = {1-8}, publisher = {Iranian Society of Instrumentation and Control Engineers}, url = {http://joc.kntu.ac.ir/article-1-207-en.html}, eprint = {http://joc.kntu.ac.ir/article-1-207-en.pdf}, journal = {Journal of Control}, issn = {2008-8345}, eissn = {2538-3752}, year = {2014} } @article{ author = {Maroufian, Seyede Sara and Abbaszadeh, Karim}, title = {Modeling and Fault Detection of an Axial Flux Permanent Magnet Motor Using Magnetic Equivalent Circuit and ARX Model}, abstract ={Investigations on modeling methods and fault detection for electrical machines have lead to different paths. The speed of the method combined with the accuracy achieved, are the goals which are being followed. Magnetic Equivalent Circuit Modeling of the Electrical Machines is one of the proposed methods and has been used for modeling of an Axial Flux Permanent Magnet Motor in this paper. The motor structure and feature are introduced. Further analysis includes determination of the Back-EMF Voltage using Magnetic Circuit Model. Detection of magnets demagnetization is established by Fourier analysis of the Back-EMF voltage. An ARX model is then fitted into the extracted input-output frequency data. Two approaches have been followed to detect PM defections. The first model will predict the generated flux of the defected PM with according to the Back-EMF voltage while the second will detect the percentage of the defection with the help of Back-EMF Fourier analysis}, Keywords = {Axail Flux PM Motor, Magnetic Equivalent Circuit, ARX Model, Fault Detection.}, volume = {7}, Number = {4}, pages = {9-18}, publisher = {Iranian Society of Instrumentation and Control Engineers}, url = {http://joc.kntu.ac.ir/article-1-201-en.html}, eprint = {http://joc.kntu.ac.ir/article-1-201-en.pdf}, journal = {Journal of Control}, issn = {2008-8345}, eissn = {2538-3752}, year = {2014} } @article{ author = {Salahshoor, Karim and Hoorfar, Farzad and Abbasinejad, Reza and Ataei, Seyed Saee}, title = {Design and Implementation of a Risk Based Maintenance Program for Determining Optimum Maintenance Intervals for Field Instruments in Sarkhun Gas Refinery}, abstract ={The main goal of performing a maintenance program is increasing of the benefit and process reliability without any negative effect on personnel safety and environmental concerns. Risk based maintenance road map reduces fault occurrence probability and as a result reduces effects of equipment failure happening (economical, environmental effects). This type of risk based planning helps much in making right and economic decision making. This paper introduces risk based maintenance plan for selected instruments in Sarkhun and Qeshm gas threatening company. By designing of an adaptive preventive maintenance strategy as an inspection program and obtaining an optimum checking interval devices risk will be reduced.}, Keywords = {Risk Based Maintenance, Optimum maintenance interval, instrument devices, Preventive maintenance, Gas refinery}, volume = {7}, Number = {4}, pages = {19-29}, publisher = {Iranian Society of Instrumentation and Control Engineers}, url = {http://joc.kntu.ac.ir/article-1-208-en.html}, eprint = {http://joc.kntu.ac.ir/article-1-208-en.pdf}, journal = {Journal of Control}, issn = {2008-8345}, eissn = {2538-3752}, year = {2014} } @article{ author = {Tavassoli, Babak and Badfar, Fari}, title = {Constrained Model Predictive Controller Design Based on Multi-parametric Programming for the Boiler Unit of a Gas Refinery}, abstract ={One of the breakthroughs in the progress of model predictive control is usage of the multi-parametric programming methods in solving the optimization problems in the constrained model predictive control algorithms to obtain explicit solutions. However, constrained model predictive control based on multi-parametric programming has not yet been applied widely in industries. In this paper, after a brief description of this method, nonlinear modeling of the boiler is considered and the obtained model is linearized at a working point. Then, the mentioned control method is applied and it is shown that the constrained model predictive control with multi-parametric programming has a much better performance with respect to the PID control, while it is computationally much faster with respect to the ordinary constrained model predictive control.}, Keywords = {Constrained Model Predictive Control, Multi-parametric Programming, Boiler Unit, Gas Refinery.}, volume = {7}, Number = {4}, pages = {31-39}, publisher = {Iranian Society of Instrumentation and Control Engineers}, url = {http://joc.kntu.ac.ir/article-1-200-en.html}, eprint = {http://joc.kntu.ac.ir/article-1-200-en.pdf}, journal = {Journal of Control}, issn = {2008-8345}, eissn = {2538-3752}, year = {2014} } @article{ author = {Dastaviz, Abbas and Ataie, Mohammad and Niroomand, Mahdi}, title = {Robust Decentralized Controller Design for Power Electronic Converters}, abstract ={This paper considers controller design for power electronic converters, which are used in hybrid energy systems. Due to the number of variables to be controlled and presence of disturbances and uncertainties, a robust decentralized controller is presented. In this regard, first, a state-space model of the two-input SEPIC, which is a buck-boost converter and conducts in continuous conduction mode, is derived. Then parametric uncertainty in the state-space matrices is represented by input perturbation, in terms of ∆-M representation. Next, the parameters of a robust decentralized PI controller are designed using μ-synthesis. Simulation results are used to verify the performance of the proposed controller.}, Keywords = {Power electronic converter, Robust control, μ synthesis, Decentralized PI controller}, volume = {7}, Number = {4}, pages = {41-52}, publisher = {Iranian Society of Instrumentation and Control Engineers}, url = {http://joc.kntu.ac.ir/article-1-209-en.html}, eprint = {http://joc.kntu.ac.ir/article-1-209-en.pdf}, journal = {Journal of Control}, issn = {2008-8345}, eissn = {2538-3752}, year = {2014} } @article{ author = {Mohammadian, Mohammad Reza and HamidiBeheshti, Mohammad Taghi and Kavousi, Kaveh}, title = {Protein Domain Folding Prediction Based on DBSCAN}, abstract ={This paper presents a density-based clustering approach for data classification of protein folding. The method is shown to perform better as compared with the conventional methods with respect to computational speed and robustness against noise. Protein clustering is known to be one of the important challenges of prediction and identification of protein’s properties and its performances. Due to recent advances in sequence detection devices, many proteins have been discovered which requires an automatic protein clustering system. An automatic protein clustering method is thus presented here which is based on folding and information extracted from the output features of the sequence. Further, fuzzy data fusion is used to combine the clustered information in order to improve the clustering performance.}, Keywords = {Density-Based Clustering, Protein-Fold Classification, Robust Clustering}, volume = {7}, Number = {4}, pages = {53-62}, publisher = {Iranian Society of Instrumentation and Control Engineers}, url = {http://joc.kntu.ac.ir/article-1-210-en.html}, eprint = {http://joc.kntu.ac.ir/article-1-210-en.pdf}, journal = {Journal of Control}, issn = {2008-8345}, eissn = {2538-3752}, year = {2014} }