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var str = 'Design of Decentralized Fractional Order PIʎ Controller for Pilot Plant Binary Didtillation Column';
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]]>
Decentralized PI controller]]>
Pilot plant binary distillation column]]>
TITO]]>
PSO]]>
Integral criterion]]>
This paper presents the application of fractional order operators to improve the control quality of multivariable systems. The basic ideas of this tuning method are based, in the first place, on the existed tuning methods for setting the parameters of the decentralized fractional order PIʎ controller for ʎ=1, which means setting the parameters of the classical decentralized PI controller, and the minimum integral criterion by using Particle Swarm Optimization (PSO) algorithm for setting the fractional integration action order ʎ. The integral criterion is formulated to improve the dynamic response of the system, while causing a good decoupling between control loops. The Distillation Column, which is a multivariable system with two inputs and two outputs (TITO), in a decentralized control structure, is analyzed. Simulation results are presented to show the control quality improvement of this proposed decentralized fractional order PIʎ controller tuning method compared to the decentralized PI controller tuned using any existed tuning method.]]>
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var str = 'BETTOU, KHALFA';
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]]>
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var str = 'CHAREF , ABDELFATEH';
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]]>
Algerian Journal of Signals and Systems ; Vol. 5 No. 1 (2020); 33-39]]>
2676-1548]]>
2543-3792]]>
10.51485/ajss.v5i1]]>
Laboratory of Signals and Systems, Algeria]]>
2020-03-15]]>
Copyright (c) 2020 KHALFA BETTOU, ABDELFATEH CHAREF]]>
https://creativecommons.org/licenses/by-nc/4.0]]>
https://ajss.dz/index.php/ajss/article/view/93/76]]>
application/pdf]]>
eng]]>
info:eu-repo/semantics/article]]>
info:eu-repo/semantics/publishedVersion]]>
Peer-reviewed Article]]>
https://ajss.dz/index.php/ajss/article/view/93]]>
10.51485/ajss.v5i1.93]]>
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var str = 'Risk Assessment of a Gas Plant (Unit 30 Skikda Refinery) Using Hazop &Bowtie Methods, Simulation of Dangerous Scenarios Using ALOHA Software';
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]]>
Safety]]>
probabilistic risk assessment]]>
outcome frequency]]>
event tree analysis]]>
Process plant and chemical processes are complex and large systems, consisting of thousands of devices interacting with each other [76][45]. The structure of this type of industrial plants lead to difficulties in process control, hence deviations from the operation objectives or desired states. These deviations creates abnormal situations that drive products out of specification, increased operational costs, shut downs and even worse they can cause accidents, which may lead to damages of equipment, environment and affect the health. identifying hazards is fundamental for ensuring the safe design and operation in process plants. Based on the idea of learning from accidents, several techniques and standards are available to identify hazardous situations and help companies to build up strategies to avoid the hazards. In this s work we present a study based on two methods BOWTIE and HAZOP methods applied for an LPG a plant for gas separation located in SKIKDA refinery which is considered as the most important refinery in Algeria where the treatment capacity reaches more than 15 millions tones per year of crude oil. Several recommendations raised from our study to improve the safety of the plant particularly since it is considered as an old plant start working since 1980. The study is completed by simulating the deduced dangerous scenarios using ALOHA software.]]>
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var str = 'BENDIB , Riad';
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]]>
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var str = 'MECHHOUD, Elarkam';
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]]>
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var str = 'BENDJAMA , Hanane';
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]]>
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var str = 'BOULKSIBAT, Halima';
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]]>
Algerian Journal of Signals and Systems ; Vol. 5 No. 1 (2020); 25-32]]>
2676-1548]]>
2543-3792]]>
10.51485/ajss.v5i1]]>
Laboratory of Signals and Systems, Algeria]]>
2020-03-15]]>
Copyright (c) 2020 Riad BENDIB , Elarkam MECHHOUD, Hanane BENDJAMA , Halima BOULKSIBAT]]>
https://creativecommons.org/licenses/by-nc/4.0]]>
https://ajss.dz/index.php/ajss/article/view/92/75]]>
application/pdf]]>
eng]]>
info:eu-repo/semantics/article]]>
info:eu-repo/semantics/publishedVersion]]>
Peer-reviewed Article]]>
https://ajss.dz/index.php/ajss/article/view/92]]>
10.51485/ajss.v5i1.92]]>
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var str = 'Analysis and Control Design for a Class of Fractional Order Time-Delay Systems';
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]]>
Fractional order control]]>
Time-delay systems]]>
Fractional PID controller]]>
Relay method]]>
Parameters adjustment]]>
In this paper, we consider a class of fractional order time-delay systems and propose a fractional order control design for their stabilization. The controller parameter’s adjustment is achieved in two steps: first, the relay approach is used to compute satisfactory classical PID coefficients, namely kp, Ti and Td. Then, the fractional orders ʎ and µ are optimized using performance criteria. Simulation results show the efficiency of the proposed design technique and its ability to enhance the PID control performance.]]>
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var str = 'BOUDANA, Marwa';
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]]>
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var str = 'LADACI, Samir';
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]]>
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var str = 'LOISEAU, Jean Jacques';
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]]>
Algerian Journal of Signals and Systems ; Vol. 5 No. 1 (2020); 18-24]]>
2676-1548]]>
2543-3792]]>
10.51485/ajss.v5i1]]>
Laboratory of Signals and Systems, Algeria]]>
2020-03-15]]>
Copyright (c) 2020 Marwa BOUDANA, Samir LADACI, Jean Jacques LOISEAU]]>
https://creativecommons.org/licenses/by-nc/4.0]]>
https://ajss.dz/index.php/ajss/article/view/91/74]]>
application/pdf]]>
eng]]>
info:eu-repo/semantics/article]]>
info:eu-repo/semantics/publishedVersion]]>
Peer-reviewed Article]]>
https://ajss.dz/index.php/ajss/article/view/91]]>
10.51485/ajss.v5i1.91]]>
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var str = 'Fuzzy LOPA for the evaluation of accident scenarios and risk reduction measures in suppler manner';
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]]>
Fuzzy LOPA]]>
Uncertain and imprecise]]>
Reduced frequencies consequence]]>
Risk assessment]]>
The analysis and evaluation of risks by the LOPA method requires the presence of certain data and information on the various risk evaluation parameters such as, the frequencies of initiating events, the probabilities failures of the security barriers and also probability of ignition .This data is generally obtained from the history of the system analyzed. In the absence or lack of data on the state of the system, other sources such as databases and expert judgment are used. Despite the fact that the choice of data is made while respecting the adaptation of this data to the system studied, based on its history and on similar systems having the same mode of operation, it seems important to emphasize the fact that imperfections are not properly taken into account. Linked to the data used by the various risk analysis methods including the LOPA method, the results are always uncertain and imprecise. To address such a problem, we use the "fuzzy LOPA" approach. As a case study, we used an operational industrial system which is a heater H-101.]]>
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var str = 'Hellas, Mohamed Seddik';
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]]>
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var str = 'Chaib, Rachid';
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]]>
Algerian Journal of Signals and Systems ; Vol. 5 No. 1 (2020); 10-17]]>
2676-1548]]>
2543-3792]]>
10.51485/ajss.v5i1]]>
Laboratory of Signals and Systems, Algeria]]>
2020-03-15]]>
Copyright (c) 2020 Mohamed Seddik Hellas, Rachid Chaib]]>
https://creativecommons.org/licenses/by-nc/4.0]]>
https://ajss.dz/index.php/ajss/article/view/90/73]]>
application/pdf]]>
eng]]>
info:eu-repo/semantics/article]]>
info:eu-repo/semantics/publishedVersion]]>
Peer-reviewed Article]]>
https://ajss.dz/index.php/ajss/article/view/90]]>
10.51485/ajss.v5i1.90]]>
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var str = 'Traffic Urban Control Using an Intelligent PSO Algorithm Based on Integrated Approach';
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]]>
PSO]]>
large scale-optimization]]>
Prediction]]>
traffic flow modelling]]>
traffic lights]]>
Petri nets]]>
In this paper, we intend to contribute to the improvement of urban traffic mobility using a learning method of traffic lights controllers. We proposed a Particle Swarm Optimization (PSO) method in which the intelligent swarm acts as the cycle time of the traffic signal. The best swarm (solution found) meets the evaluation criteria selected to describe desired objectives. The main measures of traffic lights efficiency are to maximize flow-rate at which vehicles can cross a road junction and minimize the additional travel time of the driver called vehicle delay. Particle Swarm Optimizer was coupled with the traffic flow model based on Continuous Petri nets (PN). One potential advantage of CPN model is to provide insights regarding a behavior of the platoon of vehicles on the target road network. The result obtained from this study has tested with various scenarios related to intersections in different situations. The developed self-scheduling of the optimal signal timing ensures safety and continuous traffic flow, thus increasing the mobility and reducing fuel consumption and pollutant emissions.]]>
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var str = 'DIAF, Radja';
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]]>
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var str = 'TOLBA, Cherif';
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]]>
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var str = 'Nait Sidi Moh, Ahmed';
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]]>
Algerian Journal of Signals and Systems ; Vol. 5 No. 1 (2020); 1-9]]>
2676-1548]]>
2543-3792]]>
10.51485/ajss.v5i1]]>
Laboratory of Signals and Systems, Algeria]]>
2020-03-15]]>
Copyright (c) 2020 Radja DIAF, Cherif TOLBA, Ahmed Nait Sidi Moh]]>
https://creativecommons.org/licenses/by-nc/4.0]]>
https://ajss.dz/index.php/ajss/article/view/89/72]]>
application/pdf]]>
eng]]>
info:eu-repo/semantics/article]]>
info:eu-repo/semantics/publishedVersion]]>
Peer-reviewed Article]]>
https://ajss.dz/index.php/ajss/article/view/89]]>
10.51485/ajss.v5i1.89]]>
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var str = 'Efficient lock and home security system';
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]]>
door security]]>
RFID badge]]>
smartphone]]>
GSM]]>
remotely locked/unlocked]]>
This work deals with lock and home security systems. First, Motion sensors detect movement indoors and outdoors to guard against intruders, protect valuables and more. Thus, if any movement, RFID reader will be activated and database will be scanned to identify the persons who have the access to the home. This enhances the effectiveness of the security system and provides the user with the complete, whole-house protection he needs. An RFID badge can be used to unlock the door and access to the home. Alerts also are received on the smart phone if motion is sensed in a protected area inside or outside; giving the user the information it needs to act quickly. The door can also be remotely locked/unlocked. A microcontroller (ATmega2560) is used to control the entire system, and GSM is used to send alerts to the Smartphone. An Ethernet shield that connects the microcontroller to the database (DB) is also added.]]>
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var str = 'BELAIDI, Hadjira';
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]]>
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var str = 'MEDDAH, Nour-El-Houda';
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]]>
Algerian Journal of Signals and Systems ; Vol. 4 No. 2 (2019); 112-120]]>
2676-1548]]>
2543-3792]]>
10.51485/ajss.v4i2]]>
Laboratory of Signals and Systems, Algeria]]>
2019-12-15]]>
Copyright (c) 2019 Hadjira BELAIDI, Nour-El-Houda MEDDAH]]>
https://creativecommons.org/licenses/by-nc/4.0]]>
https://ajss.dz/index.php/ajss/article/view/87/71]]>
application/pdf]]>
eng]]>
info:eu-repo/semantics/article]]>
info:eu-repo/semantics/publishedVersion]]>
Peer-reviewed Article]]>
https://ajss.dz/index.php/ajss/article/view/87]]>
10.51485/ajss.v4i2.87]]>
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var str = 'Power Quality Detection, Classification and Monitoring Using LABVIEW';
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]]>
Power quality]]>
Detection]]>
Classification]]>
Monitoring]]>
LABView]]>
In recent years, Power Quality becomes increasingly a major concern for both electric utilities and end users. Accordingly, the electrical engineering community has to deal with the analysis, diagnosis and solution of PQ issues using system approach rather than handling these issues as individual problems. This paper describes the analysis of PQ using advanced signal processing tools represented in Hilbert & Wavelet Transforms (HT-WT) and artificial intelligence tools represented in Artificial Neural Network & Support Vector Machine (ANN-SVM) for detection and classification of power quality disturbances respectively. These techniques were successfully simulated using LABVIEW software capabilities. The results of simulation indicate that the signal processing techniques are effective mechanisms to detect and classify power quality disturbances. At the end, the combination of WT as a tool of detection and features extraction with SVM as a classifier tool resulted as the best combination for PQ monitoring system.]]>
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var str = 'DEKHANDJI, Fatma Zohra';
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]]>
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var str = 'TALHAOUI, Salim';
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]]>
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var str = 'ARKAB, Youcef';
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]]>
Algerian Journal of Signals and Systems ; Vol. 4 No. 2 (2019); 101-111]]>
2676-1548]]>
2543-3792]]>
10.51485/ajss.v4i2]]>
Laboratory of Signals and Systems, Algeria]]>
2019-12-15]]>
Copyright (c) 2019 Fatma Zohra DEKHANDJI, Salim TALHAOUI, Youcef ARKAB]]>
https://creativecommons.org/licenses/by-nc/4.0]]>
https://ajss.dz/index.php/ajss/article/view/86/70]]>
application/pdf]]>
eng]]>
info:eu-repo/semantics/article]]>
info:eu-repo/semantics/publishedVersion]]>
Peer-reviewed Article]]>
https://ajss.dz/index.php/ajss/article/view/86]]>
10.51485/ajss.v4i2.86]]>
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var str = 'A Smart Metering Simulation in LABVIEW';
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]]>
Smart Grids]]>
Smart Meters]]>
Load Control]]>
LABView]]>
The smart grid delivers electricity from producers to consumers using two-way digital technology and considers the involvement of the user. The implementation of smart grids should start at the consumer side using smart meters, control devices and a communication link. Smart metering is the bridge between smart buildings and smart grids. It is viewed as a crucial factor for an efficient functioning of the internal electricity market and a successful implementation of the renewable energy and security of supply. The replacement of the currently used electromechanical meters with smart digital meters along with domestic load controllers is identified for better energy conservation at the consumer side .These devices can be remotely read and are able to measure consumption multiple times per day which is beneficial for a good demand response, customer feedback and energy management. The purpose of the present paper is to illustrate how smart meters operate and how their implementation can improve the current grid]]>
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var str = 'RECIOUI, Abdelmadjid';
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]]>
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var str = 'DJEMAI, Hassiba';
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]]>
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var str = 'BOUCENNA, Farah';
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]]>
Algerian Journal of Signals and Systems ; Vol. 4 No. 2 (2019); 89-100]]>
2676-1548]]>
2543-3792]]>
10.51485/ajss.v4i2]]>
Laboratory of Signals and Systems, Algeria]]>
2019-12-15]]>
Copyright (c) 2019 Abdelmadjid RECIOUI, Hassiba DJEMAI, Farah BOUCENNA]]>
https://creativecommons.org/licenses/by-nc/4.0]]>
https://ajss.dz/index.php/ajss/article/view/85/69]]>
application/pdf]]>
eng]]>
info:eu-repo/semantics/article]]>
info:eu-repo/semantics/publishedVersion]]>
Peer-reviewed Article]]>
https://ajss.dz/index.php/ajss/article/view/85]]>
10.51485/ajss.v4i2.85]]>
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var str = 'Predictive Maintenance Applied to Three phase Induction Motors';
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]]>
Induction machines]]>
Preventive maintenance]]>
Reliability]]>
faults]]>
Induction machines are widely used in industry. The operating conditions may sometimes lead the machine into different fault situations. The machine should be shut down when a fault is experienced to avoid complete process failure and for the safety of the workers. The predictive maintenance consists of scheduling maintenance activities only when a functional failure is detected. The advantages of predictive maintenance are accepted in many industries because of its efficiency in fault detection during early stages and thus reducing unscheduled down time. It increases productivity, improves quality and provides the feeling of safety and reliability to staff. The main types of external faults experienced by these motors are over loading; single phasing, unbalanced supply voltage, phase reversal, ground fault, under voltage and over voltage. MATLAB/SIMULINK simulation is used in this work for the detection and analysis of the faults on induction motor.]]>
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var str = 'DEKHANDJI, Fatma Zohra';
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]]>
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var str = 'HALLEDJ, Salah Eddine';
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]]>
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Algerian Journal of Signals and Systems ; Vol. 4 No. 2 (2019); 71-88]]>
2676-1548]]>
2543-3792]]>
10.51485/ajss.v4i2]]>
Laboratory of Signals and Systems, Algeria]]>
2019-12-15]]>
Copyright (c) 2019 Fatma Zohra DEKHANDJI, Salah Eddine HALLEDJ, Oussama ZABOUB]]>
https://creativecommons.org/licenses/by-nc/4.0]]>
https://ajss.dz/index.php/ajss/article/view/84/68]]>
application/pdf]]>
eng]]>
info:eu-repo/semantics/article]]>
info:eu-repo/semantics/publishedVersion]]>
Peer-reviewed Article]]>
https://ajss.dz/index.php/ajss/article/view/84]]>
10.51485/ajss.v4i2.84]]>
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var str = '3D Antenna Array Design using Firefly Optimization Algorithm';
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3D Antenna Arrays]]>
Optimization]]>
Firefly Algorithm]]>
Sidelobe level]]>
Directivity]]>
The design of antenna arrays in a 3D geometry is presented in this Chapter. The decision variables considered for this synthesis problem are the array element amplitude excitations. The objective is to design an array which ensures minimum sidelobe level and a high directivity. The synthesis process is carried out using a nature-inspired global optimization technique. The optimization method based on the reaction of a firefly to the light of other fireflies is known as Firefly Algorithm (FA). It is a population-based iterative heuristic global optimization algorithm technique, developed by Xin-She Yang, for multi-dimensional and multi-modal problems. Simulation results for an antenna array with isotropic elements show that side lobe level is significantly reduced in non-uniform case. Besides, the directivity is not worse than that of the uniform one.]]>
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var str = 'RECIOUI, Abdelmadjid';
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var str = 'GRAINAT, Youcef';
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Algerian Journal of Signals and Systems ; Vol. 4 No. 2 (2019); 61-70]]>
2676-1548]]>
2543-3792]]>
10.51485/ajss.v4i2]]>
Laboratory of Signals and Systems, Algeria]]>
2019-12-15]]>
Copyright (c) 2019 Abdelmadjid RECIOUI, Youcef GRAINAT]]>
https://creativecommons.org/licenses/by-nc/4.0]]>
https://ajss.dz/index.php/ajss/article/view/83/67]]>
application/pdf]]>
eng]]>
info:eu-repo/semantics/article]]>
info:eu-repo/semantics/publishedVersion]]>
Peer-reviewed Article]]>
https://ajss.dz/index.php/ajss/article/view/83]]>
10.51485/ajss.v4i2.83]]>