Fuzzy Control

Open Access Article

1 - SSIM-Based Fuzzy Video Rate Controller for Variable Bit Rate Applications of Scalable HEVC
Farhad Raufmehr Mehdi Rezaei

10.7508/jist.2019.03.004

Scalable High Efficiency Video Coding (SHVC) is the scalable extension of the latest video coding standard H.265/HEVC. Video rate control algorithm is out of the scope of video coding standards. Appropriate rate control algorithms are designed for various applications t More

Scalable High Efficiency Video Coding (SHVC) is the scalable extension of the latest video coding standard H.265/HEVC. Video rate control algorithm is out of the scope of video coding standards. Appropriate rate control algorithms are designed for various applications to overcome practical constraints such as bandwidth and buffering constraints. In most of the scalable video applications, such as video on demand (VoD) and broadcasting applications, encoded bitstreams with variable bit rates are preferred to bitstreams with constant bit rates. In variable bit rate (VBR) applications, the tolerable delay is relatively high. Therefore, we utilize a larger buffer to allow more variations in bitrate to provide smooth and high visual quality of output video. In this paper, we propose a fuzzy video rate controller appropriate for VBR applications of SHVC. A fuzzy controller is used for each layer of scalable video to minimize the fluctuation of QP at the frame level while the buffering constraint is obeyed for any number of layers received by a decoder. The proposed rate controller utilizes the well-known structural similarity index (SSIM) as a quality metric to increase the visual quality of the output video. The proposed rate control algorithm is implemented in HEVC reference software and comprehensive experiments are executed to tune the fuzzy controllers and also to evaluate the performance of the algorithm. Experimental results show a high performance for the proposed algorithm in terms of rate control, visual quality, and rate-distortion performance. Manuscript profile

Open Access Article

2 - Novel Automatic Clustering Technique Based on the Artificial Immune Algorithm
Seyed-Hamid Zahiri

In this paper a novel technique for automatic data clustering based on the artificial immune algorithm is proposed. The lengths of the antibodies are dynamically changed based on inter-clusters and intra-clusters distances by means of a fuzzy controller which has been a More

In this paper a novel technique for automatic data clustering based on the artificial immune algorithm is proposed. The lengths of the antibodies are dynamically changed based on inter-clusters and intra-clusters distances by means of a fuzzy controller which has been added to the immune algorithm to provide, also, a soft computing approach for data clustering. This idea leads to proper number of clusters and effective and powerful clustering process without any additional try and error efforts. Also the manual setting of the number of clusters is available in the proposed algorithm (like other unsupervised clustering approaches) after removing the fuzzy controller from the proposed clustering system. The method has been tested on the different kinds of the complex artificial data sets and well known benchmarks. The experimental results show that the performance of the proposed technique is much better than the k-means clustering algorithm (as a conventional one), specially for huge data sets with large feature vector dimensions. Furthermore, it is found that the performance of the proposed approach is comparable, sometimes better than the genetic algorithm based clustering technique (as an evolutionary clustering algorithm). Manuscript profile

Open Access Article

3 - Robust Position Control in DC Motor by Fuzzy Sliding Mode Control a Novel
M. Hendijani-Zadeh A. Yazdian Varjani M. Mohamadian

In spite of improvement of the AC drive systems still the DC drives are widely used in industry. One of the problems associated with control of DC motor which might cause unsuccessful attempts for designing a proper controller would be the time-varying nature of DC moto More

In spite of improvement of the AC drive systems still the DC drives are widely used in industry. One of the problems associated with control of DC motor which might cause unsuccessful attempts for designing a proper controller would be the time-varying nature of DC motors parameters and variables which might be changed while working with the motion systems. In these conditions, the control system will not response properly. One of the best suggested solutions to overcome this problem would be the use of sliding mode control (SMC). SMC is not sensitive to parameters changes and yet would have a fair response to the systems variations. However, SMC suffers from some deficiencies including inflexibility in controller parameters. A Better response can be achieved by SMC in compare with classical methods but it is not the most optimized response. The fair solution can be defined through faster fulfillment of target, less overshoot and more consistency of the system against the changes of the parameters. In this paper, a new fuzzy based method is presented to increase the SMC ability to reach a more convenient solution. Optimized response can be achieved in terms of shorter settling time, less overshoot, and more stability. Manuscript profile

Open Access Article

4 - Design and Simulation of Fuzzy-ANFIS Controller for Continuous Control of Transmitted Power by TCSC
A. Kargar M. Hosseinzadeh

Control of transmitted active power is an important issue in operation and management of power systems especially in congestion or fault conditions. In these situations, Thyristor Controlled Series Capacitor (TCSC) is used to continuous control and increase the transmit More

Control of transmitted active power is an important issue in operation and management of power systems especially in congestion or fault conditions. In these situations, Thyristor Controlled Series Capacitor (TCSC) is used to continuous control and increase the transmitted power due to these facts that TCSC can act dynamically and is able to stable the system during fault conditions. In this paper, the transmitted power is controlled in the ten megawatt span by using the TCSC. For this purpose, various controllers such as PID, fuzzy and Adaptive Network-based Fuzzy Interface System (ANFIS) are designed to continuous control of the transmitted power. Simulation results evaluate advantages and disadvantages these controllers. ANFIS controller is designed by open loop method which has a good transient response. However, it has a large steady state error and is very sensitive to the variations in system. Fuzzy and ANFIS controllers are combined to remove these defects. The simulation results verify the advantages of the fuzzy-ANFIS controller with respect to the other designed controllers. Manuscript profile

Open Access Article

5 - Robust Optimal Stable Fuzzy Controller Design for Stabilization of Electric Vehicle Speed, in Presence of Parametric Uncertainties and External Disturbances
Mohammad Veysi M. Shasadeghi M. R. Soltanpour

In electric vehicle’s nonlinear dynamic equations, some parameters has uncertainty such as the coefficient of rolling resistance, drag coefficient, armature resistance and field winding resistance. Design of a controller that is robust in the presence of these parametri More

In electric vehicle’s nonlinear dynamic equations, some parameters has uncertainty such as the coefficient of rolling resistance, drag coefficient, armature resistance and field winding resistance. Design of a controller that is robust in the presence of these parametric uncertainties and also in presence of external disturbances, and on the other hand simultaneously satisfies the optimality criteria, is a challenging issue. In practical applications, in addition to the above problem, the computational load of the control input should also be considered and provide a rational interaction between the controller's desirable performance and the calculations volume. In the present paper, a robust optimal stable fuzzy controller based on the parallel distributed compensation is designed, using Takagi-Sugeno fuzzy model of electric vehicle. The stabilizer feedback gains of fuzzy model, the upper bound of the uncertainties, the upper bound of the disturbances effect, and the upper bound of the cost function are obtained completely offline, through the solving of a minimization problem based on the linear matrix inequality. Therefore, the calculation volume of the control input is extremely low. This allows the practical implementation of the proposed controller. The favorable performance of the proposed controller is demonstrated in five-step simulations. Manuscript profile

Open Access Article

6 - Nonlinear Fractional Intelligent Controller for Photovoltaic Inverters
Hadi Delavari Sara Arjmandpour

<p style="text-align: justify; padding-right: 30px;"><!-- [if gte mso 9]><xml> <w:WordDocument> <w:View>Norma More

<p style="text-align: justify; padding-right: 30px;"><span style="font-size: 10.0pt; font-family: 'Times New Roman',serif; mso-fareast-font-family: 'Times New Roman'; mso-ansi-language: EN-US; mso-fareast-language: EN-US; mso-bidi-language: AR-SA;">At present, with the significant growth of energy consumption, increase of greenhouse gases and environmental pollutants, more attention is directed toward renewable energies. Renewable energies include geothermal, wind, photovoltaic energy and etc. Among the advantages of photovoltaic energy, its wide range and easy access, helping to preserve the environment, compatibility with distributed power networks, low noise, quick installation and lower cost compared to other energies can be noted. Important challenges facing photovoltaic systems are changing climatic conditions and parameters variation that affect the performance of the system. In this paper, to track the maximum power point in a photovoltaic system, a fuzzy fractional order sliding mode controller based on disturbance observer and uncertainty estimator using neural network is designed. The sliding mode control is used to reduce chattering, neural network to estimate the system uncertainties, fuzzy system to estimate the coefficient of the signum function in the control law and disturbance observer to approximate the disturbances in the system. Also, the stability of the system has been proven using the Lyapunov method. The simulation results of the photovoltaic system confirm the effectiveness of the proposed method and shows satisfactory performance.</span></p> Manuscript profile

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