Search results for: Adaptive impedance control

Authors: Fanqiang Kong, Jindong Zhang, Daiyin Zhu

Abstract:

Space-time adaptive processing (STAP) techniques have been motivated as a key enabling technology for advanced airborne radar applications. In this paper, the notion of cognitive radar is extended to STAP technique, and cognitive STAP is discussed. The principle for improving signal-to-clutter ratio (SCNR) based on slow-time coding is given, and the corresponding optimization algorithm based on cyclic and power-like algorithms is presented. Numerical examples show the effectiveness of the proposed method.

Keywords: Space-time adaptive processing (STAP), signal-to-clutter ratio, slow-time coding.

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Authors: Yang Weiping, Zhang Zhilong, Li Jicheng, Chen Zengping, He Jun

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The background estimation approach using a small window median filter is presented on the bases of analyzing IR point target, noise and clutter model. After simplifying the two-dimensional filter, a simple method of adopting one-dimensional median filter is illustrated to make estimations of background according to the characteristics of IR scanning system. The adaptive threshold is used to segment canceled image in the background. Experimental results show that the algorithm achieved good performance and satisfy the requirement of big size image-s real-time processing.

Keywords: Point target, background estimation, median filter, adaptive threshold, target detection.

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Authors: Mustafa Resa Becan

Abstract:

Sliding mode control with a fuzzy boundary layer is presented to hydraulic position control problem in this paper. A nonlinear hydraulic servomechanism which has an asymmetric cylinder is modeled and simulated first, then the proposed control scheme is applied to this model versus the conventional sliding mode control. Simulation results proved that the chattering free position control is achieved by tuning the fuzzy scaling factors properly.

Keywords: Hydraulic servomechanism, position control, sliding mode control, chattering, fuzzy boundary layer.

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Authors: S. Thongkeaw, M. Boonthienthong

Abstract:

This paper presents the techniques for voltage control in distribution system. It is integrated in the distribution management system. Voltage is an important parameter for the control of electrical power systems. The distribution network operators have the responsibility to regulate the voltage supplied to consumer within statutory limits. Traditionally, the On-Load Tap Changer (OLTC) transformer equipped with automatic voltage control (AVC) relays is the most popular and effective voltage control device. A static synchronous compensator (STATCOM) may be equipped with several controllers to perform multiple control functions. Static Var Compensation (SVC) is regulation slopes and available margins for var dispatch. The voltage control in distribution networks is established as a centralized analytical function in this paper. 

Keywords: Voltage Control, Reactive Power, Distribution System.

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Authors: Mohanad Alata , Moh'd Al-Nimr, Rami Al-Jarrah

Abstract:

The present work demonstrates the design and simulation of a fuzzy control of an air conditioning system at different pressures. The first order Sugeno fuzzy inference system is utilized to model the system and create the controller. In addition, an estimation of the heat transfer rate and water mass flow rate injection into or withdraw from the air conditioning system is determined by the fuzzy IF-THEN rules. The approach starts by generating the input/output data. Then, the subtractive clustering algorithm along with least square estimation (LSE) generates the fuzzy rules that describe the relationship between input/output data. The fuzzy rules are tuned by Adaptive Neuro-Fuzzy Inference System (ANFIS). The results show that when the pressure increases the amount of water flow rate and heat transfer rate decrease within the lower ranges of inlet dry bulb temperatures. On the other hand, and as pressure increases the amount of water flow rate and heat transfer rate increases within the higher ranges of inlet dry bulb temperatures. The inflection in the pressure effect trend occurs at lower temperatures as the inlet air humidity increases.

Keywords: Air Conditioning, ANFIS, Fuzzy Control, Sugeno System.

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Authors: Rong Zhou, Shun’ich Kaneko, Fumio Tanaka, Miyuki Kayamori, Motoshige Shimizu

Abstract:

In this paper, we propose a robust disease detection method, called adaptive orientation code matching (Adaptive OCM), which is developed from a robust image registration algorithm: orientation code matching (OCM), to achieve continuous and site-specific detection of changes in plant disease. We use two-stage framework for realizing our research purpose; in the first stage, adaptive OCM was employed which could not only realize the continuous and site-specific observation of disease development, but also shows its excellent robustness for non-rigid plant object searching in scene illumination, translation, small rotation and occlusion changes and then in the second stage, a machine learning method of support vector machine (SVM) based on a feature of two dimensional (2D) xy-color histogram is further utilized for pixel-wise disease classification and quantification. The indoor experiment results demonstrate the feasibility and potential of our proposed algorithm, which could be implemented in real field situation for better observation of plant disease development.

Keywords: Cercospora Leaf Spot (CLS), Disease detection, Image processing, Orientation Code Matching (OCM), Support Vector Machine (SVM).

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Authors: U. Yavas, M. Gokasan

Abstract:

Control of diesel engine’s air path has drawn a lot of attention due to its multi input-multi output, closed coupled, non-linear relation. Today, precise control of amount of air to be combusted is a must in order to meet with tight emission limits and performance targets. In this study, passenger car size diesel engine is modeled by AVL Boost RT, and then simulated with standard, industry level PID controllers. Finally, linear model predictive control is designed and simulated. This study shows the importance of modeling and control of diesel engines with flexible algorithm development in computer based systems.

Keywords: Predictive control, engine control, engine modeling, PID control, feedforward compensation.

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Authors: I Made Darmayuda, Chai Tshun Chuan Kevin, Je Minkyu

Abstract:

Plenty researches have reported techniques to harvest energy from piezoelectric transducer. In the earlier years, the researches mainly report linear energy harvesting techniques whereby interface circuitry is designed to have input impedance that match with the impedance of the piezoelectric transducer. In recent years non-linear techniques become more popular. The non-linear technique employs voltage waveform manipulation to boost the available-for-extraction energy at the time of energy transfer.  The fact that non-linear energy extraction provides larger available-for-extraction energy doesn’t mean the linear energy extraction is completely obsolete. In some scenarios, such as where initial power is not available, linear energy extraction is still preferred. A modified Buck Boost circuit which is capable of harvesting piezoelectric energy using both linear and non-linear techniques is reported in this paper. Efficiency of at least 64% can be achieved using this circuit. For linear extraction, the modified Buck Boost circuit is controlled using a fix frequency and duty cycle clock. A voltage sensor and a pulse generator are added as the controller for the non-linear extraction technique. 

Keywords: Buck boost, energy harvester, linear energy harvester, non-linear energy harvester, piezoelectric, synchronized charge extraction.

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Authors: Mihai Caramihai, Irina Severin

Abstract:

Bioprocesses are appreciated as difficult to control because their dynamic behavior is highly nonlinear and time varying, in particular, when they are operating in fed batch mode. The research objective of this study was to develop an appropriate control method for a complex bioprocess and to implement it on a laboratory plant. Hence, an intelligent control structure has been designed in order to produce biomass and to maximize the specific growth rate.

Keywords: Fed batch bioprocess, mass-balance model, fuzzy control

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Authors: O. Ikpotokin

Abstract:

In any production process, every product is aimed to attain a certain standard, but the presence of assignable cause of variability affects our process, thereby leading to low quality of product. The ability to identify and remove this type of variability reduces its overall effect, thereby improving the quality of the product. In case of a univariate control chart signal, it is easy to detect the problem and give a solution since it is related to a single quality characteristic. However, the problems involved in the use of multivariate control chart are the violation of multivariate normal assumption and the difficulty in identifying the quality characteristic(s) that resulted in the out of control signals. The purpose of this paper is to examine the use of non-parametric control chart (the bootstrap approach) for obtaining control limit to overcome the problem of multivariate distributional assumption and the p-value method for detecting out of control signals. Results from a performance study show that the proposed bootstrap method enables the setting of control limit that can enhance the detection of out of control signals when compared, while the p-value method also enhanced in identifying out of control variables.

Keywords: Bootstrap control limit, p-value method, out-of-control signals, p-value, quality characteristics.

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Authors: H. Zainuddin, F. Hanafi, M. H. Hairi, A. Aman, M.H.N. Talib

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This paper investigates the effects of knowledge-based acceleration feedback control integrated with Automatic Generation Control (AGC) to enhance the quality of frequency control of governing system. The Intelligent Acceleration Feedback Controller (IAFC) is proposed to counter the over and under frequency occurrences due to major load change in power system network. Therefore, generator tripping and load shedding operations can be reduced. Meanwhile, the integration of IAFC with AGC, a well known Load-Frequency Control (LFC) is essential to ensure the system frequency is restored to the nominal value. Computer simulations of frequency response of governing system are used to optimize the parameters of IAFC. As a result, there is substantial improvement on the LFC of governing system that employing the proposed control strategy.

Keywords: Knowledge-based Supplementary Control, Acceleration Feedback, Load Frequency Control, Automatic Generation Control.

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Authors: Ventzas Dimitrios, Petropoulos George

Abstract:

The paper presents a compressor anti-surge control system, that results in maximizing compressor throughput with pressure standard deviation reduction, increased safety margin between design point and surge limit line and avoiding possible machine surge. Alternative control strategies are presented.

Keywords: Anti-surge, control, compressor, PID control, safety, fault tolerance, start-up, ESD.

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Authors: S. Benchelha, H. C. Aoudjehane, M. Hakdaoui, R. El Hamdouni, H. Mansouri, T. Benchelha, M. Layelmam, M. Alaoui

Abstract:

The logistic regression (LR) and multivariate adaptive regression spline (MarSpline) are applied and verified for analysis of landslide susceptibility map in Oudka, Morocco, using geographical information system. From spatial database containing data such as landslide mapping, topography, soil, hydrology and lithology, the eight factors related to landslides such as elevation, slope, aspect, distance to streams, distance to road, distance to faults, lithology map and Normalized Difference Vegetation Index (NDVI) were calculated or extracted. Using these factors, landslide susceptibility indexes were calculated by the two mentioned methods. Before the calculation, this database was divided into two parts, the first for the formation of the model and the second for the validation. The results of the landslide susceptibility analysis were verified using success and prediction rates to evaluate the quality of these probabilistic models. The result of this verification was that the MarSpline model is the best model with a success rate (AUC = 0.963) and a prediction rate (AUC = 0.951) higher than the LR model (success rate AUC = 0.918, rate prediction AUC = 0.901).

Keywords: Landslide susceptibility mapping, regression logistic, multivariate adaptive regression spline, Oudka, Taounate, Morocco.

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Authors: Ali Zifan, Mohammad Hassan Moradi, Sohrab Saberi, Farzad Towhidkhah

Abstract:

Electrocardiogram (ECG) segmentation is necessary to help reduce the time consuming task of manually annotating ECG-s. Several algorithms have been developed to segment the ECG automatically. We first review several of such methods, and then present a new single lead segmentation method based on Adaptive piecewise constant approximation (APCA) and Piecewise derivative dynamic time warping (PDDTW). The results are tested on the QT database. We compared our results to Laguna-s two lead method. Our proposed approach has a comparable mean error, but yields a slightly higher standard deviation than Laguna-s method.

Keywords: Adaptive Piecewise Constant Approximation, Dynamic programming, ECG segmentation, Piecewise DerivativeDynamic Time Warping.

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Authors: Alexandre Boum, Salomon Madinatou

Abstract:

This paper aims at bringing a scientific contribution to the cardiac arrhythmia biomedical diagnosis systems; more precisely to the study of the amelioration of cardiac arrhythmia classification performance using artificial neural network, adaptive neuro-fuzzy and fuzzy inference systems classifiers. The purpose of this amelioration is to enable cardiologists to make reliable diagnosis through automatic cardiac arrhythmia analyzes and classifications based on high confidence classifiers. In this study, six classes of the most commonly encountered arrhythmias are considered: the Right Bundle Branch Block, the Left Bundle Branch Block, the Ventricular Extrasystole, the Auricular Extrasystole, the Atrial Fibrillation and the Normal Cardiac rate beat. From the electrocardiogram (ECG) extracted parameters, we constructed a matrix (360x360) serving as an input data sample for the classifiers based on neural networks and a matrix (1x6) for the classifier based on fuzzy logic. By varying three parameters (the quality of the neural network learning, the data size and the quality of the input parameters) the automatic classification permitted us to obtain the following performances: in terms of correct classification rate, 83.6% was obtained using the fuzzy logic based classifier, 99.7% using the neural network based classifier and 99.8% for the adaptive neuro-fuzzy based classifier. These results are based on signals containing at least 360 cardiac cycles. Based on the comparative analysis of the aforementioned three arrhythmia classifiers, the classifiers based on neural networks exhibit a better performance.

Keywords: Adaptive neuro-fuzzy, artificial neural network, cardiac arrythmias, fuzzy inference systems.

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Authors: Phongsak Phakamach

Abstract:

A DC servomotor position control system using a Fuzzy Logic Sliding mode Model Following Control or FLSMFC approach is presented. The FLSMFC structure consists of an integrator and variable structure system. The integral control is introduced into it in order to eliminated steady state error due to step and ramp command inputs and improve control precision, while the fuzzy control would maintain the insensitivity to parameter variation and disturbances. The FLSMFC strategy is implemented and applied to a position control of a DC servomotor drives. Experimental results indicated that FLSMFC system performance with respect to the sensitivity to parameter variations is greatly reduced. Also, excellent control effects and avoids the chattering phenomenon.

Keywords: Sliding mode model following control, fuzzy logic, DC servomotor.

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Authors: Mihai Caramihai Ana A Chirvase, Irina Severin

Abstract:

Bioprocesses are appreciated as difficult to control because their dynamic behavior is highly nonlinear and time varying, in particular, when they are operating in fed batch mode. The research objective of this study was to develop an appropriate control method for a complex bioprocess and to implement it on a laboratory plant. Hence, an intelligent control structure has been designed in order to produce biomass and to maximize the specific growth rate.

Keywords: Fed batch bioprocess, mass-balance model, fuzzy control.

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Authors: Sophia Fry, Mahir Irtiza, Alexa Hoffman, Yousef Sardahi

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This study presents an intelligent control algorithm for a flexible robotic arm. Fuzzy control is used to control the motion of the arm to maintain the arm tip at the desired position while reducing vibration and increasing the system speed of response. The Fuzzy controller (FC) is based on adding the tip angular position to the arm deflection angle and using their sum as a feedback signal to the control algorithm. This reduces the complexity of the FC in terms of the input variables, number of membership functions, fuzzy rules, and control structure. Also, the design of the fuzzy controller is model-free and uses only our knowledge about the system. To show the efficacy of the FC, the control algorithm is implemented on the flexible joint manipulator (FJM) developed by Quanser. The results show that the proposed control method is effective in terms of response time, overshoot, and vibration amplitude.

Keywords: Fuzzy logic control, model-free control, flexible joint manipulators, nonlinear control.

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Authors: Ali Zifan, Sohrab Saberi, Mohammad Hassan Moradi, Farzad Towhidkhah

Abstract:

Electrocardiogram (ECG) segmentation is necessary to help reduce the time consuming task of manually annotating ECG's. Several algorithms have been developed to segment the ECG automatically. We first review several of such methods, and then present a new single lead segmentation method based on Adaptive piecewise constant approximation (APCA) and Piecewise derivative dynamic time warping (PDDTW). The results are tested on the QT database. We compared our results to Laguna's two lead method. Our proposed approach has a comparable mean error, but yields a slightly higher standard deviation than Laguna's method.

Keywords: Adaptive Piecewise Constant Approximation, Dynamic programming, ECG segmentation, Piecewise Derivative Dynamic Time Warping.

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Authors: Seungsuk Ha, Youngjoon Han, Hernsoo Hahn

Abstract:

This paper proposes a method of adaptively generating a gait pattern of biped robot. The gait synthesis is based on human's gait pattern analysis. The proposed method can easily be applied to generate the natural and stable gait pattern of any biped robot. To analyze the human's gait pattern, sequential images of the human's gait on the sagittal plane are acquired from which the gait control values are extracted. The gait pattern of biped robot on the sagittal plane is adaptively generated by a genetic algorithm using the human's gait control values. However, gait trajectories of the biped robot on the sagittal plane are not enough to construct the complete gait pattern because the biped robot moves on 3-dimension space. Therefore, the gait pattern on the frontal plane, generated from Zero Moment Point (ZMP), is added to the gait one acquired on the sagittal plane. Consequently, the natural and stable walking pattern for the biped robot is obtained.

Keywords: Biped robot, gait pattern, genetic algorithm.

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Authors: Teodora Bakardjieva, Galya Gercheva

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In this paper an open agent-based modular framework for personalized and adaptive curriculum generation in e-learning environment is proposed. Agent-based approaches offer several potential advantages over alternative approaches. Agent-based systems exhibit high levels of flexibility and robustness in dynamic or unpredictable environments by virtue of their intrinsic autonomy. The presented framework enables integration of different types of expert agents, various kinds of learning objects and user modeling techniques. It creates possibilities for adaptive e-learning process. The KM e-learning system is in a process of implementation in Varna Free University and will be used for supporting the educational process at the University.

Keywords: agents, e-Learning, knowledge management, knowledge sharing, artificial intelligence

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Authors: Sheren H. Salah, Ahmed Y. Ben Sasi

Abstract:

The inverted pendulum system is a classic control problem that is used in universities around the world. It is a suitable process to test prototype controllers due to its high non-linearities and lack of stability. The inverted pendulum represents a challenging control problem, which continually moves toward an uncontrolled state. This paper presents the possibility of balancing an inverted pendulum system using sliding mode control (SMC). The goal is to determine which control strategy delivers better performance with respect to pendulum’s angle and cart's position. Therefore, proportional-integral-derivative (PID) is used for comparison. Results have proven SMC control produced better response compared to PID control in both normal and noisy systems.

Keywords: Inverted pendulum (IP) proportional-integralderivative (PID), sliding mode control (SMC).

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Authors: Mohammed Ibrahim M, Anupama R.

Abstract:

Robustness is one of the primary performance criteria for an Intelligent Video Surveillance (IVS) system. One of the key factors in enhancing the robustness of dynamic video analysis is,providing accurate and reliable means for shadow detection. If left undetected, shadow pixels may result in incorrect object tracking and classification, as it tends to distort localization and measurement information. Most of the algorithms proposed in literature are computationally expensive; some to the extent of equalling computational requirement of motion detection. In this paper, the homogeneity property of shadows is explored in a novel way for shadow detection. An adaptive division image (which highlights homogeneity property of shadows) analysis followed by a relatively simpler projection histogram analysis for penumbra suppression is the key novelty in our approach.

Keywords: homogeneity, penumbra, projection histogram, shadow correction

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Authors: Vinti Davar

Abstract:

Background: Worldwide, at least 2.8 million people die each year as a result of being overweight or obese, and 35.8 million (2.3%) of global DALYs are caused by overweight or obesity. Obesity is acknowledged as one of the burning public health problems reducing life expectancy and quality of life. The body composition analysis of the university population is essential in assessing the nutritional status, as well as the risk of developing diseases associated with abnormal body fat content so as to make nutritional recommendations. Objectives: The main aim was to determine the prevalence of obesity and overweight in University students using Anthropometric analysis and BIA methods. Material and Methods: In this cross-sectional study, 283 university students participated. The body composition analysis was undertaken by using mainly: i) Anthropometric Measurement: Height, Weight, BMI, waist circumference, hip circumference and skin fold thickness, ii) Bio-electrical impedance was used for analysis of body fat mass, fat percent and visceral fat which was measured by Tanita SC-330P Professional Body Composition Analyzer. The data so collected were compiled in MS Excel and analyzed for males and females using SPSS 16. Results and Discussion: The mean age of the male (n= 153) studied subjects was 25.37 ±2.39 years and females (n=130) was 22.53 ±2.31. The data of BIA revealed very high mean fat per cent of the female subjects i.e. 30.3±6.5 per cent whereas mean fat per cent of the male subjects was 15.60±6.02 per cent indicating a normal body fat range. The findings showed high visceral fat of both males (12.92±3.02) and females (16.86±4.98). BMI, BF% and WHR were higher among females, and BMI was higher among males. The most evident correlation was verified between BF% and WHR for female students (r=0.902; p<0.001). The correlation of BFM and BF% with thickness of triceps, sub scapular and abdominal skin folds and BMI was significant (P<0.001). Conclusion: The studied data made it obvious that there is a need to initiate lifestyle changing strategies especially for adult females and encourage them to improve their dietary intake to prevent incidence of noncommunicable diseases due to obesity and high fat percentage.

Keywords: Anthropometry, bioelectrical impedance, body fat percentage, obesity.

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Authors: Francisco Aparisi, Marco A. de Luna

Abstract:

In some real applications of Statistical Process Control it is necessary to design a control chart to not detect small process shifts, but keeping a good performance to detect moderate and large shifts in the quality. In this work we develop a new quality control chart, the synthetic T2 control chart, that can be designed to cope with this objective. A multi-objective optimization is carried out employing Genetic Algorithms, finding the Pareto-optimal front of non-dominated solutions for this optimization problem.

Keywords: Multi-objective optimization, Quality Control, SPC, Synthetic T2 control chart.

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Authors: P. Georgieva, S. Feyo de Azevedo

Abstract:

This paper is focused on issues of process modeling and two model based control strategies of a fed-batch sugar crystallization process applying the concept of artificial neural networks (ANNs). The control objective is to force the operation into following optimal supersaturation trajectory. It is achieved by manipulating the feed flow rate of sugar liquor/syrup, considered as the control input. The control task is rather challenging due to the strong nonlinearity of the process dynamics and variations in the crystallization kinetics. Two control alternatives are considered – model predictive control (MPC) and feedback linearizing control (FLC). Adequate ANN process models are first built as part of the controller structures. MPC algorithm outperforms the FLC approach with respect to satisfactory reference tracking and smooth control action. However, the MPC is computationally much more involved since it requires an online numerical optimization, while for the FLC an analytical control solution was determined.

Keywords: artificial neural networks, nonlinear model control, process identification, crystallization process

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Authors: Daniel M. Muntean, Viorel Ungureanu

Abstract:

More than half of the urban population in Romania lives today in residential buildings made out of large prefabricated reinforced concrete panels. Since their initial design was made in the 1960’s, these housing units are now being technically and morally outdated, consuming large amounts of energy for heating, cooling, ventilation and lighting, while failing to meet the needs of the contemporary life-style. Due to their widespread use, the design of a system that improves their energy efficiency would have a real impact, not only on the energy consumption of the residential sector, but also on the quality of life that it offers. Furthermore, with the transition of today’s existing power grid to a “smart grid”, buildings could become an active element for future electricity networks by contributing in micro-generation and energy storage. One of the most addressed issues today is to find locally adapted strategies that can be applied considering the 20-20-20 EU policy criteria and to offer sustainable and innovative solutions for the cost-optimal energy performance of buildings adapted on the existing local market. This paper presents a possible adaptive design scenario towards sustainable retrofitting of these housing units. The apartments are transformed in order to meet the current living requirements and additional extensions are placed on top of the building, replacing the unused roof space, acting not only as housing units, but as active solar energy collection systems. An adaptive building envelope is ensured in order to achieve overall air-tightness and an elevator system is introduced to facilitate access to the upper levels.

Keywords: Adaptive building, energy efficiency, retrofitting, residential buildings, smart grid.

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Authors: Ε. Giovanis

Abstract:

In this paper we apply an Adaptive Network-Based Fuzzy Inference System (ANFIS) with one input, the dependent variable with one lag, for the forecasting of four macroeconomic variables of US economy, the Gross Domestic Product, the inflation rate, six monthly treasury bills interest rates and unemployment rate. We compare the forecasting performance of ANFIS with those of the widely used linear autoregressive and nonlinear smoothing transition autoregressive (STAR) models. The results are greatly in favour of ANFIS indicating that is an effective tool for macroeconomic forecasting used in academic research and in research and application by the governmental and other institutions

Keywords: Linear models, Macroeconomics, Neuro-Fuzzy, Non-Linear models

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Authors: Megha Rao, Søren H. Jensen, Xiufu Sun, Anke Hagen, Mogens B. Mogensen

Abstract:

Solid oxide electrolysis cells have an immense potential in converting CO₂ and H₂O into syngas during co-electrolysis operation. The produced syngas can be further converted into hydrocarbons. This kind of technology is called power-to-gas or power-to-liquid. To produce hydrocarbons via this route, durability of the cells is still a challenge, which needs to be further investigated in order to improve the cells. In this work, various nickel-yttria stabilized zirconia (Ni-YSZ) fuel electrode supported or YSZ electrolyte supported cells, cerium gadolinium oxide (CGO) barrier layer, and an oxygen electrode are investigated for durability under co-electrolysis conditions in both galvanostatic and potentiostatic conditions. While changing the gas on the oxygen electrode, keeping the fuel electrode gas composition constant, a change in the gas concentration arc was observed by impedance spectroscopy. Measurements of open circuit potential revealed the presence of leaks in the setup. It is speculated that the change in concentration impedance may be related to the leaks. Furthermore, the cells were also tested under pressurized conditions to find an inter-play between the leak rate and the pressure. A mathematical modeling together with electrochemical and microscopy analysis is presented.

Keywords: Co-electrolysis, solid oxide electrolysis cells, leaks, durability, gas concentration.

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Authors: Hassan Zarei, Ali Vahidian Kamyad, Sohrab Effati

Abstract:

In this paper, a mathematical model of human immunodeficiency virus (HIV) is utilized and an optimization problem is proposed, with the final goal of implementing an optimal 900-day structured treatment interruption (STI) protocol. Two type of commonly used drugs in highly active antiretroviral therapy (HAART), reverse transcriptase inhibitors (RTI) and protease inhibitors (PI), are considered. In order to solving the proposed optimization problem an adaptive memetic algorithm with population management (AMAPM) is proposed. The AMAPM uses a distance measure to control the diversity of population in genotype space and thus preventing the stagnation and premature convergence. Moreover, the AMAPM uses diversity parameter in phenotype space to dynamically set the population size and the number of crossovers during the search process. Three crossover operators diversify the population, simultaneously. The progresses of crossover operators are utilized to set the number of each crossover per generation. In order to escaping the local optima and introducing the new search directions toward the global optima, two local searchers assist the evolutionary process. In contrast to traditional memetic algorithms, the activation of these local searchers is not random and depends on both the diversity parameters in genotype space and phenotype space. The capability of AMAPM in finding optimal solutions compared with three popular metaheurestics is introduced.

Keywords: HIV therapy design, memetic algorithms, adaptivealgorithms, nonlinear integer programming.

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