تطبیق

Open Access Article

1 - A Novel Proposed Algorithm to Tackle Glasses Wearing and Beard Issues in Facial IR Recognition
H. Komari Alaie M. Khademi

20.1001.1.16823745.1390.9.1.1.8

Face recognition via thermal infrared images is a modern recognition method. It has been so interesting for many researchers during last ten years. This method which operates via thermal features and the situation of human face vessels has much more benefits than visual More

Face recognition via thermal infrared images is a modern recognition method. It has been so interesting for many researchers during last ten years. This method which operates via thermal features and the situation of human face vessels has much more benefits than visual-based methods. In these images, the effect of environmental lights changes, which is one of the most important obstacles of face recognition via visual images, is totally eliminated. The most important face recognition problem via thermal infrared images is the existence of diffusion obstacles like glasses and beard, which block the exact extraction of the situation of face vessels. Considering the suggested algorithm, these problems have been completely solved. In this paper face recognition is done through face vessels. For extraction of the face features, the situation of vessel branches is used. Also by choosing appropriate classification, fake vessels and false branches has been omitted. On the other hand, the best feature is extracted by using Dynamic Time Wrapping algorithm which is resistant to nonlinear changes. The simulation on UTK-IRIS gallery set has showed the accurate recognition rate 95% on the images with glasses and 88% on the images with beard, so the proposed method has improved the recognition rate about 10% and 44% respectively on same gallery set compared with the best other works. Manuscript profile

Open Access Article

2 - Adaptive Control of Pitch Angle of Wind Turbine Using Human Brain Mechanisms of Emotional Learning
M. Hayatdavudi mohsen Farshad H. R. Najafi R. Sedaghati M. Joorabian

20.1001.1.16823745.1392.11.1.2.3

The purpose of this paper is optimal location of distributed generation in electric distribution networks. Load uncertainty and desired voltage range has been modeled using fuzzy data theory. The objective function includes loss reduction, improvement of profile index a More

The purpose of this paper is optimal location of distributed generation in electric distribution networks. Load uncertainty and desired voltage range has been modeled using fuzzy data theory. The objective function includes loss reduction, improvement of profile index and voltage stability index with their relevant constraints, voltage constraints and transmittable power from the line. Load variation has been shown for three different time durations (peak, off peak and average).PSO technique has been used to optimize the objective function while Max-Min method has been applied to select the answer. Results produced from the proposed model have been provided in 5 different scenarios on a 33 bus system of IEEE. Manuscript profile

Open Access Article

3 - Designing an Adaptive Sliding-Mode Controller for Car Active Suspension System Using an Optimal logarithmic Sliding Surface
S. A. Zahiripour R. Tafaghodi A. A. Jalali S. K. Mousavi Mashhadi

In this paper, a quarter car active suspension system with a hydraulic actuator, has been controlled by sliding mode coupled with an adaptive approach. To deal with all kinds of uncertainty arising from the effect of external perturbation or the any nonlinear behavior s More

In this paper, a quarter car active suspension system with a hydraulic actuator, has been controlled by sliding mode coupled with an adaptive approach. To deal with all kinds of uncertainty arising from the effect of external perturbation or the any nonlinear behavior system, sliding mode control has been used. In the proposed method the sliding surface, by using an optimal strategy to minimize the optimal cost function is derived, so the result is a logarithmic sliding surface. Adaptive algorithms proposed in this paper because of the nonlinear variability by time and not bounded uncertainty in the system. While the effects of parameter uncertainties and external disturbances to system performance have been dramatically reduced, the stability of control system proves based on the Lyapanof theory. The proposed control method has been done on a quarter car active suspension system with a hydraulic actuator. Simulation results of the proposed method show that the activation of suspension system by the proposed method increases its performance compare with the passive suspension system. Manuscript profile

Open Access Article

4 - A Formal Framework for Dynamic Reconfiguration in Adaptive Systems
J. Karimpour R. Alyari

20.1001.1.16823745.1394.13.2.2.9

Today's advanced systems are expected to be able to adapt to environmental conditions and unpredictable situations. The first requirement for such systems is to adjust them according to customer needs, their own ability and operational environment and they should be abl More

Today's advanced systems are expected to be able to adapt to environmental conditions and unpredictable situations. The first requirement for such systems is to adjust them according to customer needs, their own ability and operational environment and they should be able to answer when faced with problem and unexpected request. Software adaptation techniques try to cope, with adaptation contracts and reconfiguration capabilities. Also these reconfigurations should be performed out of the sight of client and sometimes during the operation so that prohibit system designers from direct involvement in the internal affairs of clients. Sometimes these adaptation techniques have an impressive role in reusing components for making new systems or improving old ones. Thins paper try to create a system that can be adapted to the environment and besides it also reduces the complexity problem. To do so, at first we use a formal model to represent the whole system and then, build a mathematical model called adaptor based on adaptation contract and client requests. After creation of the adaptor, the all configuration and transactions between the client and system are done through the adaptors and Adaptors are responsible for coordinating the internal system components. Also, to avoid complexity, the concept of hierarchical networks and services are used for building the networks of adaptors. Manuscript profile

Open Access Article

5 - Learners Grouping in Adaptive Learning Systems Using Fuzzy Grafting Clustering
M. S. Rezaei Gh. A. Montazer

20.1001.1.16823745.1394.13.4.5.6

Quality of adaptive and collaborative learning systems is related to appropriate specifying learners and accuracy of separation learners in homogenous and heterogeneous groups. In the proposed method for learners grouping, researchers effort to improving basic clusterin More

Quality of adaptive and collaborative learning systems is related to appropriate specifying learners and accuracy of separation learners in homogenous and heterogeneous groups. In the proposed method for learners grouping, researchers effort to improving basic clustering methods by combination of them and improving methods. This work makes the complexity of grouping methods increased and quality of result’s groups decreased. In this paper, new method for selection appropriate clusters based on fuzzy theory is proposed. In this method, each cluster is defined as a fuzzy set and the corresponding clusters are determined. So the best cluster is selected among each corresponding clusters. The results of an empirical evaluation of the proposed method based on two criteria: “Davies-Bouldin” and “Purity and Gathering” indicate that this method has better performance than other clustering methods such as FCM, K-means, hybrid clustering method (HCM), evolutionary fuzzy clustering (EFC) and ART neural network. Manuscript profile

Open Access Article

6 - Improving Q-Learning Using Simultaneous Updating and Adaptive Policy Based on Opposite Action
M. Pouyan S. Golzari A. Mousavi Ahmad Hatam

20.1001.1.16823745.1395.14.2.15.9

Q-learning is a one of the most popular and frequently used model-free reinforcement learning method. Among the advantages of this method is independent in its prior knowledge and there is a proof for its convergence to the optimal policy. One of the main limitations of More

Q-learning is a one of the most popular and frequently used model-free reinforcement learning method. Among the advantages of this method is independent in its prior knowledge and there is a proof for its convergence to the optimal policy. One of the main limitations of this method is its low convergence speed, especially when the dimension is high. Accelerating convergence of this method is a challenge. Q-learning can be accelerated the convergence by the notion of opposite action. Since two Q-values are updated simultaneously at each learning step. In this paper, adaptive policy and the notion of opposite action are used to speed up the learning process by integrated approach. The methods are simulated for the grid world problem. The results demonstrate a great advance in the learning in terms of success rate, the percent of optimal states, the number of steps to goal, and average reward. Manuscript profile

Open Access Article

7 - Design and Implementation of a New Adaptive Sliding Mode for Current Control in Islanding Mode Operation
M. M. Ghanbarian M. Nayeripour A. H. Rajaei

20.1001.1.16823745.1395.14.3.5.1

This paper proposes a new modified adaptive sliding mode controller in order to control the inverters of DGS in the voltage and current (power) control modes in a microgrid. An observer is used to estimate the uncertain parameters in controller design and considering t More

This paper proposes a new modified adaptive sliding mode controller in order to control the inverters of DGS in the voltage and current (power) control modes in a microgrid. An observer is used to estimate the uncertain parameters in controller design and considering these estimated values, the controller is adapted to new condition. In the power management strategy, one of inverter controls the voltage and the other inverter controls the load current and balances the active power. Due to delays in startup power electronic converter and sliding mode controller, the result of controller implementation with classical controllers does not meet the requirement and so, considering these delays with adaptive controller, the performance will be improved considerably and the reference signal will be tracked with lower steady state error in comparison with classical sliding mode controller. Moreover, this controller reduces the total harmonic distortion and improves the rms and peak value tracking. Implementation of system using DSP/TMS320F28335 as well as MATLAB simulation validates the performance of system in different conditions. Manuscript profile

Open Access Article

8 - An Adaptive Incremental Conductance MPPT Based on BELBIC Controller in Photovoltaic Systems
S. Azimi Sardari B. Mirzaeian Dehkordi M. Niroomand

20.1001.1.16823745.1396.15.2.5.6

Many conventional incremental conductance (INC) methods are applied for maximum power point tracking (MPPT) of photovoltaic arrays. Where, the optimization step size determines the speed of MPPT. Fast tracking could be achieved with bigger increments but the system migh More

Many conventional incremental conductance (INC) methods are applied for maximum power point tracking (MPPT) of photovoltaic arrays. Where, the optimization step size determines the speed of MPPT. Fast tracking could be achieved with bigger increments but the system might not operate properly at the MPP and might become oscillated at this point; therefore, there is a trade-off between the time needed to reach the MPP and the oscillation error. This article is to present an adaptive optimization step size in the INC to improve solar array performance. To adjust the MPP in the photovoltaic (PV) operation point, brain emotional learning based intelligent controller (BELBIC) is applied as an adaptive optimization step size in the INC. This would considerably increase the system's accuracy. The effectiveness of this proposed method is verified by comparing its simulation and experimental results with the conventional methods in different operating conditions. Manuscript profile

Open Access Article

9 - Performance Analysis of Subband Adaptive Algorithms over Distributed Networks Based on Incremental Strategy
Mohammad S. E. Abadi A. R. Danaee M. S. Shafiee

20.1001.1.16823745.1397.16.3.2.2

This paper presents the problem of distributed estimation in an incremental network based on the family of normalized subband adaptive algorithms (NSAAs). The distributed NSAA (dNSAA), the distributed selective partial update NSAA (dSPU-NSAA), the distributed dynamic se More

This paper presents the problem of distributed estimation in an incremental network based on the family of normalized subband adaptive algorithms (NSAAs). The distributed NSAA (dNSAA), the distributed selective partial update NSAA (dSPU-NSAA), the distributed dynamic selection NSAA (dDS-NSAA), and the dSPU-DS-NSAA are introduced in a unified way. The dNSAAs have better convergence speed than distributed normalized least mean square (dNLMS) algorithm especially for colored Gaussian input of the nodes. In comparison with dNSAA, the dSPU-NSAA, and dDS-NSAA have lower computational complexity and close performance to dNSAA. Also by combination of these algorithms, the dSPU-DS-NSAA is established which is computationally efficient. In addition, a unified approach for mean-square performance analysis of each individual node is presented. This approach can be used to establish a performance analysis of classical distributed adaptive algorithms as well. The theoretical expressions for transient, and steady-state performance analysis of the various dNSAAs are introduced. The validity of the theoretical results, and the good performance of these algorithms are demonstrated by several computer simulations. Manuscript profile

Open Access Article

10 - Close Loop Identification for Combustion System by Recurrent Adaptive Neuro-Fuzzy Inference System and Network with Exogenous Inputs
E. Aghadavoodi G. Shahgholian

20.1001.1.16823745.1397.16.3.7.7

Boiler-turbine is a multi-variable and complicated system in steam power plants including combustion, temperature and drum water level. Selecting control loops as a unique loop in order to identify and control the boiler as a whole unit is a difficult and complicated ta More

Boiler-turbine is a multi-variable and complicated system in steam power plants including combustion, temperature and drum water level. Selecting control loops as a unique loop in order to identify and control the boiler as a whole unit is a difficult and complicated task, because of nonlinear time variant dynamic characteristics of the boiler. It is necessary to identify each control group in order to accomplish a realistic and effective model, appropriate for designing an efficient controller. Both the effective and efficient performance of the identified model during the load change is of major importance. Here, not all parts of the system should be considered as a unit part, if determining and effective and realistic model is sought. The combustion loop of the 320 MW steam power plant of Islam Abad, Isfahan is the subject. Due to the sensitivity and complexity of the system, with respect to its nonlinear and closed loop characteristics, the identification of the system is conducted through intelligent procedures like recurrent adaptive neuro-fuzzy inference system (RANFIS) and nonlinear autoregressive model with exogenous input (NARX). The comparisons of the findings with actual data collected from the plant are presented and the accuracy of the procedures is determined. Manuscript profile

Open Access Article

11 - Balancing the DC Bus Voltage of a Cascaded H-Bridge Converter with Adaptive Carrier Phase Shift Method
M. Rahali Asl M. Saradarzadeh A. R. Namadmalan

20.1001.1.16823745.1398.17.2.5.0

The cascaded H-bridge converter is one of the useful multilevel converters for high power applications. The unbalancing of cells DC bus voltages is a major issue in this topology especially when the capacitors are charged from the grid, which mainly is caused by the dif More

The cascaded H-bridge converter is one of the useful multilevel converters for high power applications. The unbalancing of cells DC bus voltages is a major issue in this topology especially when the capacitors are charged from the grid, which mainly is caused by the different losses of cells. In this paper a new method is proposed for balancing the cells DC bus voltages without need to measure the cells current. This method is named as “adaptive carrier phase shift”, which is based on the phase shift pulse width modulation. The balancing between the cells DC bus voltages is achieved by measuring the voltages and changing the carrier phase shift. This method is analyzed mathematically and is used to balance a 7-level cascaded H-bridge STATCOM. The feasibility and appropriate function of balancing method is investigated by the simulation studies in the MATLAB/Simulink software. Manuscript profile

Open Access Article

12 - Family of Variable Step-Size Affine Projection Adaptive Algorithms in Diffusion Distributed Networks
Mohammad S. E. Abadi E. Heydari

20.1001.1.16823745.1398.17.3.12.9

Distributed processing uses local computations at each node and communications among neighboring nodes to solve the problems over the entire network. Diffusion is one of the methods for performing distributed networks. This paper presents a novel Variable Step-Size Diff More

Distributed processing uses local computations at each node and communications among neighboring nodes to solve the problems over the entire network. Diffusion is one of the methods for performing distributed networks. This paper presents a novel Variable Step-Size Diffusion Affine Projection Algorithm (VSS-DAPA) to improve the performance of the Diffusion Affine Projection Algorithm (DAPA) in distributed networks. The variable step-size of each node is obtained by minimizing the Mean-Square Deviation (MSD) in that node. In comparison with Diffusion Affine Projection Algorithm (DAPA), the VSS-DAPA algorithm has faster convergence speed and lower steady-state error. To reduce the computational complexity of VSS-DAPA, the Variable Step-Size Selective Regressors Diffusion Affine Projection Algorithm (VSS-SR-DAPA), the Variable Step-Size Dynamic Selection of Diffusion Affine Projection Algorithm (VSS-DS-DAPA) and Variable Step-Size Selective Partial Update Diffusion Affine Projection Algorithm (VSS-SPU-DAPA) are proposed. Simulation results show the good performance of proposed algorithms in convergence speed and steady-state error. Manuscript profile

Open Access Article

13 - Adaptive Non-singular Terminal Sliding Mode Control Based On Disturbance Observer for the Microelectromechanical Vibratory Gyroscope Contro
M. R. Soltanpour

20.1001.1.16823745.1398.17.4.2.1

In this paper, an adaptive non-singular terminal sliding mode control based on disturbance observer is proposed for detection process and control of the micro-electromechanical vibratory gyroscope stimulation process. For this purpose, the dynamical equations of the vib More

In this paper, an adaptive non-singular terminal sliding mode control based on disturbance observer is proposed for detection process and control of the micro-electromechanical vibratory gyroscope stimulation process. For this purpose, the dynamical equations of the vibrational gyroscope system are initially expressed. In the following, the dynamical equations of this system are transmitted to the domain of state-space equations and then to the domain of tracking error. After that, the dynamic structure of the finite time disturbance observer is presented. Then, the design of the adaptive non-singular terminal sliding mode control based on finite time disturbance observer is expressed. The proposed strategy carries out the control of the stimulation process in the presence of structured and un-structured uncertainties existing in the dynamic equations of the microelectromechanical vibrational gyroscope system, and performs the detection process through only an adaptive law. The mathematical proof shows that the closed-loop system with the proposed control, and in the presence of the existing uncertainties, has the finite time global asymptotic stability. The presence of a disturbance observer in the proposed control structure will weaken the role of un-structured uncertainties in the gyroscope control process and reduce the control input amplitude. In order to evaluate the proposed control performance, simulations in 3 steps are implemented on the electromechanical vibrational gyroscope system. Simulation results confirm the desired performance of the proposed control. Manuscript profile

Open Access Article

14 - Robust Optimal Control of Lateral Vehicle’s Dynamics with Adaptive Dynamic Programming Approach
Mohammad Reza Satouri Abolhassan Razminia Arash Marashian

20.1001.1.16823745.1398.17.4.8.7

Lateral vehicle’s control with constant longitudinal velocity using adaptive dynamic programming, backstepping and zero-sum games theory is investigated in this paper. The nonlinear dynamics is considered and the steering torque is chosen to be the control input instead More

Lateral vehicle’s control with constant longitudinal velocity using adaptive dynamic programming, backstepping and zero-sum games theory is investigated in this paper. The nonlinear dynamics is considered and the steering torque is chosen to be the control input instead of the steering angle. At first, a subsystem is created by augmenting the lateral vehicle’s dynamics with lane keeping ones considering the steering angle as the control input and the road curvature as a disturbance. Utilizing adaptive dynamic programming, neural networks and zero-sum games theory, the optimal control law is obtained and then, the results exerted on the second subsystem which is the dynamics of the steering angle and a control law is captured for which using the backstepping control method. Finally, performance of the proposed algorithm is demonstrated by applying it on a typical vehicle model. Manuscript profile

Open Access Article

15 - Design and Implementation of Fuzzy Sliding Mode Controller for Motion Control of an Electric Shake Table Using Adaptive Extended Kalman Filter
Nima rajabi Ramazan Havangi

20.1001.1.16823745.1400.19.2.6.5

In this paper, Design of a fuzzy sliding mode controller (FSMC) with adaptive extended Kalman filter (AEKF) for controlling a shake table system with electric actuator and ball-screw mechanism. Due to the uncertainties regarding the model parameters and the noise of the More

In this paper, Design of a fuzzy sliding mode controller (FSMC) with adaptive extended Kalman filter (AEKF) for controlling a shake table system with electric actuator and ball-screw mechanism. Due to the uncertainties regarding the model parameters and the noise of the data of the two encoder and accelerometer sensors, there are many problems in controlling this system. Therefore, it is crucial to employ a non-precise model-based controller and a nonlinear adaptive filter. The fuzzy sliding mode control and Extended Kalman filter are a good way to control this system. In sliding mode control, chattering at the control input is inevitable. In this paper, a simple fuzzy inference mechanism is used to reduce the undesirable phenomenon of chattering by correctly estimating the upper bound of uncertainty. In the following, a recursive method is used to determine the system and measurement noise covariance matrices. The data of the two encoder and accelerometer sensors are combined in the adaptive extended Kalman filter and the results in noise elimination and parameter estimation are investigated. Linear speed feedback available through the Kalman filter is used to stabilize and control the closed loop system. The end is examined to check the performance of the control structure provided by the seismic table test. The results show that the proposed method is very effective. Manuscript profile

Open Access Article

16 - Non-Fragile Adaptive Sliding-Mode Observer Design for a Class of Fractional-Order Pseudo-Linear Systems with State Delay
مجيد پرويزيان خسرو خانداني وحيد جوهري مجد

20.1001.1.16823745.1400.19.4.1.4

In recent years, fractional order systems and fractional order control have increasingly attracted the attention of researchers in various fields of science and engineering. On the other hand, numerous control approaches have been extended in order to be utilized in fra More

In recent years, fractional order systems and fractional order control have increasingly attracted the attention of researchers in various fields of science and engineering. On the other hand, numerous control approaches have been extended in order to be utilized in fractional order systems. Despite this fact, few research studies have been devoted to generalizing integer order observers to fractional order ones. Since the applications of fractional order systems are increasing, developing fractional order observers seems to be essential. In this paper the problem of non-fragile adaptive sliding mode observer design for a class of fractional-order nonlinear systems with time delay is addressed. First, the states of the fractional-order pseudo-linear time-delay system with matched nonlinearity are estimated employing the sliding mode control method. Then the state estimation problem of fractional order systems with mismatched nonlinearity has been investigated. The asymptotic stability of the estimation error dynamics is proven by employing the Lyapunov stability analysis method for fractional order systems. The sufficient stability conditions are derived in the form of Linear Matrix Inequalities (LMIs). Eventually, the effective performance of the proposed approach in this paper has been corroborated through simulation of a numerical example and also a case study of a fractional order economic system. Manuscript profile

Open Access Article

17 - Server Based QoE Improvement for Streamed Video Content in Cloud Architecture
seyed hassan nabavi Mohammad behdadfar Mohammad Reza noorifard

20.1001.1.16823745.1399.18.2.16.8

One of the new solutions playing an important role in improving multimedia delivery quality, is applying cloud based networks. In this paper, a new cloud based scheme is proposed for improving user quality of experience in video adaptive streaming services over HTTP. In More

One of the new solutions playing an important role in improving multimedia delivery quality, is applying cloud based networks. In this paper, a new cloud based scheme is proposed for improving user quality of experience in video adaptive streaming services over HTTP. In proposed solution, a server side look ahead window algorithm and a client side HTTP-GET request transmission algorithm are applied. Using both algorithms concurrently at server side and client side, results in reducing buffer overflow probability which leads to prevent playout stall. Manuscript profile

Open Access Article

18 - Robust Finite-Time Chattering Free Sliding Mode Adaptive Impedance controller in Remote Control System in Presence of Random Delay
Abolfazl Kamali Ardakani Hadi Safdarkhani

20.1001.1.16823745.1401.20.2.11.7

Remote control of robots is one of the most relevant and practical fields in robotics. Most of the control structures of remote operation systems seek to achieve transparency and stability at the same time, which the simultaneous achievement of the both, considering the More

Remote control of robots is one of the most relevant and practical fields in robotics. Most of the control structures of remote operation systems seek to achieve transparency and stability at the same time, which the simultaneous achievement of the both, considering the uncertainty and disturbances in the system and random delay in the communication channel is very challenging. So far, many researchers have used position, speed, force or impedance information to provide various control methods, but none of these methods have achieved complete transparency and robust stability in the presence of random delay and uncertainties and disturbances and compromises between them should be made. In this paper, using a new method, a control structure including sliding mode control, adaptive control and impedance control is presented. This method has been simulated by Simulink of MATLAB software and it has been shown that this method is able to establish ideal transparency and ensure robust stability in the system with disturbances and uncertainties in the presence of random delay in the network. Manuscript profile

Open Access Article

19 - Introducing Intelligent Mutation Method Based on PSO Algorithm to Solve the Feature Selection Problem
Mahmoud Parandeh Mina Zolfy Lighvan jafar tanha

20.1001.1.16823745.1401.20.3.4.2

Today, with the increase in data production volume, attention to machine learning algorithms to extract knowledge from raw data has increased. Raw data usually has redundant or irrelevant features that affect the performance of learning algorithms. Feature selection alg More

Today, with the increase in data production volume, attention to machine learning algorithms to extract knowledge from raw data has increased. Raw data usually has redundant or irrelevant features that affect the performance of learning algorithms. Feature selection algorithms are used to improve efficiency and reduce the computational cost of machine learning algorithms. A variety of methods for selecting features are provided. Among the feature selection methods are evolutionary algorithms that have been considered because of their global optimization power. Many evolutionary algorithms have been proposed to solve the feature selection problem, most of which have focused on the target space. The problem space can also provide vital information for solving the feature selection problem. Since evolutionary algorithms suffer from the pain of not leaving the local optimal point, it is necessary to provide an effective mechanism for leaving the local optimal point. This paper uses the PSO evolutionary algorithm with a multi-objective function. In the proposed algorithm, a new mutation method that uses the particle feature score is proposed along with elitism to exit the local optimal points. The proposed algorithm is tested on different datasets and examined with existing algorithms. The simulation results show that the proposed method has an error reduction of 20%, 11%, 85%, and 7% in the Isolet, Musk, Madelon, and Arrhythmia datasets, respectively, compared to the new RFPSOFS method. Manuscript profile

Open Access Article

20 - Neural-Fuzzy Network and Z-Source Converter Adaptive Controller for Control the Power of the Hybrid Network Consisting of Doubly-Fed Induction Generator and Solar Cel
ali akbar habibi borzou yousefi abdolreza noori shirazi Mohammad rezvani

20.1001.1.16823745.1401.20.3.11.9

Renewable energies outfitted with low latency assets as wind turbines and photovoltaic exhibits give significant adverse consequences through power framework dynamic protections. For this issue, in view of fostering a high voltage direct current (HVDC) interface, a vers More

Renewable energies outfitted with low latency assets as wind turbines and photovoltaic exhibits give significant adverse consequences through power framework dynamic protections. For this issue, in view of fostering a high voltage direct current (HVDC) interface, a versatile Neuro-Fuzzy-based damping regulator is introduced in this paper for working on unique execution of low inertia resources associated with power frameworks. The created power framework comprises of various age sources including seaward and inland wind turbines (WTs), photovoltaic exhibits (PVs) and limited doubly fed induction generators (DFIGs) which are incorporated together through an interconnected framework. For this situation, thinking about various functional and innovative conditions, damping execution of proposed ANFIS plot is assessed. The proposed plot is a non-model-based regulator which utilizes the benefits of both neural and fluffy rationales together for giving a quick and secure design of damping regulator through continuous recreations. To research ANFIS plot through genuine cases, considering a commonplace microgrid comprises of various low-latency assets (for example WT, PV, DFIG), the framework damping exhibitions through hamper occasions are assessed. Recreation results demonstrate viability and effectiveness of the proposed plot for damping dynamic motions of low inertia resources with high damping proportions with respect to extreme issue occasions. Manuscript profile

Open Access Article

21 - Improving Robotic Arm Control via Model Reference Adaptive Controller Using EMG Signals Classification
Mahsa Barfi Hamidreza Karami Elham Farahi Fatemeh ّّFaridi Seyed Manouchehr Hosseini Pilangorgi

20.1001.1.16823745.1401.20.3.12.0

The purpose of designing and manufacturing prosthetic organs is to create their maximum behavioral similarity to human organs. The aim of this paper is to improve the robotic arm control via Model Reference Adaptive System (MRAS) based on Lyapunov theory using EMG data More

The purpose of designing and manufacturing prosthetic organs is to create their maximum behavioral similarity to human organs. The aim of this paper is to improve the robotic arm control via Model Reference Adaptive System (MRAS) based on Lyapunov theory using EMG data classification. In this paper, human arm is modeled with a robot with two degrees of freedom. The proposed control method is MRAS. The outcome of this research is a robotic arm with MRAS, using the classification of electromyogram (EMG) data recorded from human arm movements, results in proper tracking of the reference signal, less overshoot and steady-state error compared to the conventional PI controller. For this purpose, using two electrodes, EMG data is collected from the anterior deltoid and middle deltoid muscles of the arm of five female athletes and by performing two movements of abduction and flexion of the arm. Then, after eliminating noise, integral of absolute value (IAV), zero crossing (ZC), variance (VAR) and median frequency (MF) are extracted. Then, classification is done by linear discriminant analysis (LDA) method to detect movements based on data characteristics. Finally, the proposed controller and model are designed according to the EMG characteristics to achieve the proper control response and the appropriate command signal is sent to the controller to perform the corresponding movement. The results and the values of the obtained errors show the conformity of the model and controller behavior with the predefined movement pattern. Manuscript profile

Open Access Article

22 - Performance Enhancement of Unfalsified Adaptive Control Using the Model Reference
Mojtaba Nouri Manzar

20.1001.1.16823745.1401.20.4.12.2

Unfalsified adaptive control is a new approach in supervisory control that ensures the selection of a stabilizing controller from a control set based on the system input-output data. A prerequisite for ensuring stability is the existence of a pre-designed controller set More

Unfalsified adaptive control is a new approach in supervisory control that ensures the selection of a stabilizing controller from a control set based on the system input-output data. A prerequisite for ensuring stability is the existence of a pre-designed controller set that contains a stabilizing controller. The supervisor selects the controller based on the cost function calculated with the system input-output data. In this method, the control system performance is restricted to the controllers of the control set. In this paper, the controller set update is performed by introducing the concept of performance falsification along with the stability falsification of the active controller. To falsify the performance of the controller set, the structure of the model reference is proposed to evaluate the performance of the control system. In case of performance falsification, a new controller is designed and added to the controller set based on system data and without using any model. To design the controller, a linear matrix inequality problem is solved. In this paper, no system model is used, and the presented method is completely model-free and data-oriented. The simulation results show the performance improvement of the proposed method compared to other methods in a standard robust adaptive benchmark system. Manuscript profile

Open Access Article

23 - Ontology Matching Based on Maintaining Local Similarity of Information Using Propagation Technique
NazarMohammad Parsa Asieh Ghanbarpour

20.1001.1.16823745.1402.21.2.8.1

In recent years, ontologies, as one of the most important components of the semantic web, have expanded in various fields. The problem of ontology matching has been raised with the aim of creating a set of mappings between entities of ontologies. This problem is classif More

In recent years, ontologies, as one of the most important components of the semantic web, have expanded in various fields. The problem of ontology matching has been raised with the aim of creating a set of mappings between entities of ontologies. This problem is classified as an NP-hard problem. Therefore, greedy methods have been proposed to solve it in different ways. Selecting the appropriate lexical, structural and semantic similarity criteria and using an effective combination method to obtain the final mapping is one of the most important challenges of these methods. In this paper, an automatic method of matching ontologies is proposed to provide a one-to-one mapping set. This method detects primary mappings based on a new lexical similarity criterion, which is accordance with the descriptive essence of entities and combining this similarity with semantic similarity obtained from external semantic sources. By locally propagating the score of initial mappings in the class hierarchy graph, structurally matching entities are identified. In this method, property matching is examined in a separate step. In the final step, the mapping filter is applied in order to maintain the consistency of the final mapping set. In the evaluation section, comparing the performance of the lexical similarity measure compared to other proposed textual similarity measures, indicates the efficiency of this measure in the problem of ontology matching. In addition, the results of the proposed matching system compared to the results of the set of participating systems in the OAEI competitions shows this system in the second place and higher than many complex matching systems. Manuscript profile

Open Access Article

24 - Friendship Selection Based on Social Features in Social Internet of Things
Mohammad Mahdian S.Mojtaba Matinkhah

The Social Internet of Things (SIoT) network is the result of the union of the Social Network and the Internet of Things network; wherein, each object tries to use the services provided by its friends. In this network, to find the right friend in order to use the right More

The Social Internet of Things (SIoT) network is the result of the union of the Social Network and the Internet of Things network; wherein, each object tries to use the services provided by its friends. In this network, to find the right friend in order to use the right service is demanding. Great number of objects' friends, in classical algorithms, causes increasing the computational time and load of network navigation to find the right service with the help of friendly objects. In this article, in order to reduce the computational load and network navigation, it is proposed, firstly, to select the appropriate object friend from a heuristic approach; secondly, to use an adapted binary cuckoo optimization algorithm (AB-COA) which tries to select the appropriate friendly object to receive the service according to the maximum response capacity of each friendly object, and finally, adopting the Adamic-Adar local index (AA) with the interest degree centrality criterion so that it represents the characteristics of the common neighbors of the objects are involved in the friend selection. Finally, by executing the proposed algorithm on the Web-Stanford dataset, an average of 4.8 steps was obtained for reaching a service in the network, indicating the superiority of this algorithm over other algorithms. Manuscript profile

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