Search results for: cost-based topology and sizing optimization
1385 Improvement over DV-Hop Localization Algorithm for Wireless Sensor Networks
Authors: Shrawan Kumar, D. K. Lobiyal
Abstract:
In this paper, we propose improved versions of DVHop algorithm as QDV-Hop algorithm and UDV-Hop algorithm for better localization without the need for additional range measurement hardware. The proposed algorithm focuses on third step of DV-Hop, first error terms from estimated distances between unknown node and anchor nodes is separated and then minimized. In the QDV-Hop algorithm, quadratic programming is used to minimize the error to obtain better localization. However, quadratic programming requires a special optimization tool box that increases computational complexity. On the other hand, UDV-Hop algorithm achieves localization accuracy similar to that of QDV-Hop by solving unconstrained optimization problem that results in solving a system of linear equations without much increase in computational complexity. Simulation results show that the performance of our proposed schemes (QDV-Hop and UDV-Hop) is superior to DV-Hop and DV-Hop based algorithms in all considered scenarios.Keywords: Wireless sensor networks, Error term, DV-Hop algorithm, Localization.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 22431384 A Novel Design of a Low Cost Wideband Wilkinson Power Divider
Authors: A. Sardi, J. Zbitou, A. Errkik, L. El Abdellaoui, A. Tajmouati, M. Latrach.
Abstract:
This paper presents analysis and design of a wideband Wilkinson power divider for wireless applications. The design is accomplished by transforming the lengths and impedances of the quarter wavelength sections of the conventional Wilkinson power divider into U-shaped sections. The designed power divider is simulated by using ADS Agilent technologies and CST microwave studio software. It is shown that the proposed power divider has simple topology and good performances in terms of insertion loss, port matching and isolation at all operating frequencies (1.8 GHz, 2.45 GHz and 3.55 GHz).
Keywords: ADS Agilent technologies, CST microwave Studio, Microstrip, Wideband, Wilkinson power divider.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 57191383 A Timed and Colored Petri Nets for Modeling and Verifying Cloud System Elasticity
Authors: W. Louhichi, M.Berrima, N. Ben Rajeb Robbana
Abstract:
Elasticity is the essential property of cloud computing. As the name suggests, it constitutes the ability of a cloud system to adjust resource provisioning in relation to fluctuating workloads. There are two types of elasticity operations, vertical and horizontal. In this work, we are interested in horizontal scaling, which is ensured by two mechanisms; scaling in and scaling out. Following the sizing of the system, we can adopt scaling in the event of over-supply and scaling out in the event of under-supply. In this paper, we propose a formal model, based on temporized and colored Petri nets (TdCPNs), for the modeling of the duplication and the removal of a virtual machine from a server. This model is based on formal Petri Nets (PNs) modeling language. The proposed models are edited, verified, and simulated with two examples implemented in colored Petri nets (CPNs)tools, which is a modeling tool for colored and timed PNs.
Keywords: Cloud computing, elasticity, elasticity controller, petri nets, scaling in, scaling out.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 6051382 Design of a Permanent Magnet Synchronous Machine for the Hybrid Electric Vehicle
Authors: Arash Hassanpour Isfahani, Siavash Sadeghi
Abstract:
Permanent magnet synchronous machines are known as a good candidate for hybrid electric vehicles due to their unique merits. However they have two major drawbacks i.e. high cost and small speed range. In this paper an optimal design of a permanent magnet machine is presented. A reduction of permanent magnet material for a constant torque and an extension in speed and torque ranges are chosen as the optimization aims. For this purpose the analytical model of the permanent magnet synchronous machine is derived and the appropriate design algorithm is devised. The genetic algorithm is then employed to optimize some machine specifications. Finally the finite element method is used to validate the designed machine.Keywords: Design, Finite Element, Hybrid electric vehicle, Optimization, Permanent magnet synchronous machine.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 40941381 Experimental Measurements of Evacuated Enclosure Thermal Insulation Effectiveness for Vacuum Flat Plate Solar Thermal Collectors
Authors: Paul Henshall, Philip Eames, Roger Moss, Stan Shire, Farid Arya, Trevor Hyde
Abstract:
Encapsulating the absorber of a flat plate solar thermal collector in vacuum by an enclosure that can be evacuated can result in a significant increase in collector performance and achievable operating temperatures. This is a result of the thermal insulation effectiveness of the vacuum layer surrounding the absorber, as less heat is lost during collector operation. This work describes experimental thermal insulation characterization tests of prototype vacuum flat plate solar thermal collectors that demonstrate the improvement in absorber heat loss coefficients. Furthermore, this work describes the selection and sizing of a getter, suitable for maintaining the vacuum inside the enclosure for the lifetime of the collector, which can be activated at low temperatures.
Keywords: Vacuum, thermal, flat-plate solar collector.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 16111380 Neural Network Controller for Mobile Robot Motion Control
Authors: Jasmin Velagic, Nedim Osmic, Bakir Lacevic
Abstract:
In this paper the neural network-based controller is designed for motion control of a mobile robot. This paper treats the problems of trajectory following and posture stabilization of the mobile robot with nonholonomic constraints. For this purpose the recurrent neural network with one hidden layer is used. It learns relationship between linear velocities and error positions of the mobile robot. This neural network is trained on-line using the backpropagation optimization algorithm with an adaptive learning rate. The optimization algorithm is performed at each sample time to compute the optimal control inputs. The performance of the proposed system is investigated using a kinematic model of the mobile robot.Keywords: Mobile robot, kinematic model, neural network, motion control, adaptive learning rate.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 33171379 Optimization of a New Three-Phase High Voltage Power Supply for Industrial Microwaves Generators with N Magnetrons by Phase (Treated Case N=1)
Authors: M. Bassoui, M. Ferfra, M. Chraygane, M. Ould Ahmedou, N. Elghazal, A. Belhaiba
Abstract:
Currently, the High voltage power supply for microwave generators with one magnetron uses a single-phase transformer with magnetic shunt. To contribute in the development of technological innovation in industry of manufacturing of power supplies of magnetrons for microwaves, ovens for domestic or industrial use, this original work treats the optimization of a new three-phase high voltage power supply for industrial microwaves generators with N magnetrons by phase (Treated case N=1), from its modeling with Matlab-Simulink. The design of this power supply uses three π quadruple models equivalents of new three-phase transformer with magnetic shunt of each phase. Every one supplies at its output a voltage doubler cell composed of a capacitor and a diode that in its output supplies only one magnetron. In this work we will define a strategy that aims to reduce the volume of the transformer and the weight and cost of the entire system of the high voltage power supply, while respecting the conditions recommended by the manufacturer, concerning the current flowing in each magnetron: (Imax <1.2 A, IAv ≈ 300 mA).
Keywords: Optimization, Three-phase transformer, Modeling, power supply, magnetrons, Matlab Simulink, High Voltage
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 27921378 An Augmented Automatic Choosing Control with Constrained Input Using Weighted Gradient Optimization Automatic Choosing Functions
Authors: Toshinori Nawata
Abstract:
In this paper we consider a nonlinear feedback control called augmented automatic choosing control (AACC) for nonlinear systems with constrained input using weighted gradient optimization automatic choosing functions. Constant term which arises from linearization of a given nonlinear system is treated as a coefficient of a stable zero dynamics. Parameters of the control are suboptimally selected by maximizing the stable region in the sense of Lyapunov with the aid of a genetic algorithm. This approach is applied to a field excitation control problem of power system to demonstrate the splendidness of the AACC. Simulation results show that the new controller can improve performance remarkably well.
Keywords: Augmented automatic choosing control, nonlinear control, genetic algorithm, zero dynamics.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 18301377 The Design, Development, and Optimization of a Capacitive Pressure Sensor Utilizing an Existing 9 DOF Platform
Authors: Andrew Randles, Ilker Ocak, Cheam Daw Don, Navab Singh, Alex Gu
Abstract:
Nine Degrees of Freedom (9 DOF) systems are already in development in many areas. In this paper, an integrated pressure sensor is proposed that will make use of an already existing monolithic 9 DOF inertial MEMS platform. Capacitive pressure sensors can suffer from limited sensitivity for a given size of membrane. This novel pressure sensor design increases the sensitivity by over 5 times compared to a traditional array of square diaphragms while still fitting within a 2 mm x 2 mm chip and maintaining a fixed static capacitance. The improved design uses one large diaphragm supported by pillars with fixed electrodes placed above the areas of maximum deflection. The design optimization increases the sensitivity from 0.22 fF/kPa to 1.16 fF/kPa. Temperature sensitivity was also examined through simulation.Keywords: Capacitive pressure sensor, 9 DOF, 10 DOF, sensor, capacitive, inertial measurement unit, IMU, inertial navigation system, INS.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 23171376 Functional and Efficient Query Interpreters: Principle, Application and Performances’ Comparison
Authors: Laurent Thiry, Michel Hassenforder
Abstract:
This paper presents a general approach to implement efficient queries’ interpreters in a functional programming language. Indeed, most of the standard tools actually available use an imperative and/or object-oriented language for the implementation (e.g. Java for Jena-Fuseki) but other paradigms are possible with, maybe, better performances. To proceed, the paper first explains how to model data structures and queries in a functional point of view. Then, it proposes a general methodology to get performances (i.e. number of computation steps to answer a query) then it explains how to integrate some optimization techniques (short-cut fusion and, more important, data transformations). It then compares the functional server proposed to a standard tool (Fuseki) demonstrating that the first one can be twice to ten times faster to answer queries.Keywords: Data transformation, functional programming, information server, optimization.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 7381375 Optimal Tuning of a Fuzzy Immune PID Parameters to Control a Delayed System
Authors: S. Gherbi, F. Bouchareb
Abstract:
This paper deals with the novel intelligent bio-inspired control strategies, it presents a novel approach based on an optimal fuzzy immune PID parameters tuning, it is a combination of a PID controller, inspired by the human immune mechanism with fuzzy logic. Such controller offers more possibilities to deal with the delayed systems control difficulties due to the delay term. Indeed, we use an optimization approach to tune the four parameters of the controller in addition to the fuzzy function; the obtained controller is implemented in a modified Smith predictor structure, which is well known that it is the most efficient to the control of delayed systems. The application of the presented approach to control a three tank delay system shows good performances and proves the efficiency of the method.
Keywords: Delayed systems, Fuzzy Immune PID, Optimization, Smith predictor.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 22061374 Time-Domain Simulations of the Coupled Dynamics of Surface Riding Wave Energy Converter
Authors: Chungkuk Jin, Moo-Hyun Kim, HeonYong Kang
Abstract:
A surface riding (SR) wave energy converter (WEC) is designed and its feasibility and performance are numerically simulated by the author-developed floater-mooring-magnet-electromagnetics fully-coupled dynamic analysis computer program. The biggest advantage of the SR-WEC is that the performance is equally effective even in low sea states and its structural robustness is greatly improved by simply riding along the wave surface compared to other existing WECs. By the numerical simulations and actuator testing, it is clearly demonstrated that the concept works and through the optimization process, its efficiency can be improved.Keywords: Computer simulation, electromagnetics fully-coupled dynamics, floater-mooring-magnet, optimization, performance evaluation, surface riding, wave energy converter.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 6711373 Evaluation of Optimal Transfer Capability in Power System Interconnection
Authors: Jin-O Kim, Hyun-Il Son
Abstract:
As the electrical power industry is restructured, the electrical power exchange is becoming extended. One of the key information used to determine how much power can be transferred through the network is known as available transfer capability (ATC). To calculate ATC, traditional deterministic approach is based on the severest case, but the approach has the complexity of procedure. Therefore, novel approach for ATC calculation is proposed using cost-optimization method in this paper, and is compared with well-being method and risk-benefit method. This paper proposes the optimal transfer capability of HVDC system between mainland and a separated island in Korea through these three methods. These methods will consider production cost, wheeling charge through HVDC system and outage cost with one depth (N-1 contingency)
Keywords: ATC, power system interconnection, well-being method, cost-optimization method, risk-benefit analysis, outage cost.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 16141372 Optimization of End Milling Process Parameters for Minimization of Surface Roughness of AISI D2 Steel
Authors: Pankaj Chandna, Dinesh Kumar
Abstract:
The present work analyses different parameters of end milling to minimize the surface roughness for AISI D2 steel. D2 Steel is generally used for stamping or forming dies, punches, forming rolls, knives, slitters, shear blades, tools, scrap choppers, tyre shredders etc. Surface roughness is one of the main indices that determines the quality of machined products and is influenced by various cutting parameters. In machining operations, achieving desired surface quality by optimization of machining parameters, is a challenging job. In case of mating components the surface roughness become more essential and is influenced by the cutting parameters, because, these quality structures are highly correlated and are expected to be influenced directly or indirectly by the direct effect of process parameters or their interactive effects (i.e. on process environment). In this work, the effects of selected process parameters on surface roughness and subsequent setting of parameters with the levels have been accomplished by Taguchi’s parameter design approach. The experiments have been performed as per the combination of levels of different process parameters suggested by L9 orthogonal array. Experimental investigation of the end milling of AISI D2 steel with carbide tool by varying feed, speed and depth of cut and the surface roughness has been measured using surface roughness tester. Analyses of variance have been performed for mean and signal-to-noise ratio to estimate the contribution of the different process parameters on the process.
Keywords: D2 Steel, Orthogonal Array, Optimization, Surface Roughness, Taguchi Methodology.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 27531371 AI-Based Approaches for Task Offloading, Resource Allocation and Service Placement of IoT Applications: State of the Art
Authors: Fatima Z. Cherhabil, Mammar Sedrati, Sonia-Sabrina Bendib
Abstract:
In order to support the continued growth, critical latency of IoT applications and various obstacles of traditional data centers, Mobile Edge Computing (MEC) has emerged as a promising solution that extends the cloud data-processing and decision-making to edge devices. By adopting a MEC structure, IoT applications could be executed locally, on an edge server, different fog nodes or distant cloud data centers. However, we are often faced with wanting to optimize conflicting criteria such as minimizing energy consumption of limited local capabilities (in terms of CPU, RAM, storage, bandwidth) of mobile edge devices and trying to keep high performance (reducing response time, increasing throughput and service availability) at the same time. Achieving one goal may affect the other making Task Offloading (TO), Resource Allocation (RA) and Service Placement (SP) complex processes. It is a nontrivial multi-objective optimization problem to study the trade-off between conflicting criteria. The paper provides a survey on different TO, SP and RA recent Multi-Objective Optimization (MOO) approaches used in edge computing environments, particularly Artificial Intelligent (AI) ones, to satisfy various objectives, constraints and dynamic conditions related to IoT applications.
Keywords: Mobile Edge Computing, Multi-Objective Optimization, Artificial Intelligence Approaches, Task Offloading, Resource Allocation, Service Placement.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 4621370 Identifying Autism Spectrum Disorder Using Optimization-Based Clustering
Authors: Sharifah Mousli, Sona Taheri, Jiayuan He
Abstract:
Autism spectrum disorder (ASD) is a complex developmental condition involving persistent difficulties with social communication, restricted interests, and repetitive behavior. The challenges associated with ASD can interfere with an affected individual’s ability to function in social, academic, and employment settings. Although there is no effective medication known to treat ASD, to our best knowledge, early intervention can significantly improve an affected individual’s overall development. Hence, an accurate diagnosis of ASD at an early phase is essential. The use of machine learning approaches improves and speeds up the diagnosis of ASD. In this paper, we focus on the application of unsupervised clustering methods in ASD, as a large volume of ASD data generated through hospitals, therapy centers, and mobile applications has no pre-existing labels. We conduct a comparative analysis using seven clustering approaches, such as K-means, agglomerative hierarchical, model-based, fuzzy-C-means, affinity propagation, self organizing maps, linear vector quantisation – as well as the recently developed optimization-based clustering (COMSEP-Clust) approach. We evaluate the performances of the clustering methods extensively on real-world ASD datasets encompassing different age groups: toddlers, children, adolescents, and adults. Our experimental results suggest that the COMSEP-Clust approach outperforms the other seven methods in recognizing ASD with well-separated clusters.
Keywords: Autism spectrum disorder, clustering, optimization, unsupervised machine learning.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 3211369 Ammonia Removal from Nitrogenous Industrial Waste Water Using Iranian Natural Zeolite of Clinoptilolite Type
Authors: M.M. Jafarpour, Ar. Foolad, M.K. Mansouri, Z. Nikbakhsh, H. Saeedizade
Abstract:
Ammonia nitrogen is one of the most hazardous water pollutants, discharging into water receptors through industrial effluents. Negative environmental impacts of such chemical species in hydrosphere include accelerated eutrophication, water toxicity and harming the aquatics. Natural zeolite clinoptilolite has very high selectivity & capacity for ammonium cation sorption. It occurs in high abundances and rich mines of this zeolite exist in different parts of Iran and thus are available more cheaply and with different sizing. The aim of this study is to investigate ammonia nitrogen removal over this natural sorbent from real samples of high polluted wastewater discharging from a fertilizer producing plant. The experimental results showed that this natural sorbent without even any pre treatment system & with the same particle size available in Iranian markets has still high capability & selectivity in ammonia nitrogen removal both in batch and continuous tests.Keywords: Ammonia nitrogen removal, Clinoptilolite, Naturalzeolite, Waste water.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 33771368 Optimization of Enzymatic Activities in Malting of Oat
Authors: E. Hosseini, M. Kadivar, M. Shahedi
Abstract:
Malting is usually carried out on intact barley seed, while hull is still attached to it. In this study, oat grain with and without hull was subjected to controlled germination to optimize its enzymes activity, in such a way that lipase has the lowest and α- amylase and proteinase the highest activities. Since pH has a great impact on the activity of the enzymes, the pH of germination media was set up to 3 to 8. In dehulled oats, lipase and α-amylase had the lowest and highest activities in pHs 3 and 6, respectively whereas the highest proteinase activity was evidenced at pH 7 and 4 in the oats with and without hull respectively. While measurements indicated that the effect of hull on the enzyme activities particularly in lipase and amylase at each level of the pH are significantly different, the best results were obtained in those samples in which their hull had been removed. However, since the similar lipase activity in germinated dehulled oat were recorded at the pHs 4 and 5, therefore it was concluded that pH 5 in dehulled oat seed may provide the optimum enzyme activity for all the enzymes.Keywords: Enzyme activity, malting, oat, optimization.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 29101367 Optimal Distribution of Lift Gas in Gas Lifted Oil Field Using MPC and Unscented Kalman Filter
Authors: Roshan Sharma, Bjørn Glemmestad
Abstract:
In gas lifted oil fields, the lift gas should be distributed optimally among the wells which share gas from a common source to maximize total oil production. One of the objectives of the paper is to show that a linear MPC consisting of a control objective and an economic objective can be used both as an optimizer and a controller for gas lifted systems. The MPC is based on linearized model of the oil field developed from first principles modeling. Simulation results show that the total oil production is increased by 3.4%. Difficulties in accurately measuring the bottom hole pressure using sensors in harsh operating conditions can be resolved by using an Unscented Kalman Filter (UKF) for estimation. In oil fields where input disturbance (total supply of gas) is not measured, UKF can also be used for disturbance estimation. Increased total oil production due to optimization leads to increased profit.
Keywords: gas lift, MPC, oil production, optimization, Unscented Kalman filter.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 26451366 Artificial Neural Network Modeling and Genetic Algorithm Based Optimization of Hydraulic Design Related to Seepage under Concrete Gravity Dams on Permeable Soils
Authors: Muqdad Al-Juboori, Bithin Datta
Abstract:
Hydraulic structures such as gravity dams are classified as essential structures, and have the vital role in providing strong and safe water resource management. Three major aspects must be considered to achieve an effective design of such a structure: 1) The building cost, 2) safety, and 3) accurate analysis of seepage characteristics. Due to the complexity and non-linearity relationships of the seepage process, many approximation theories have been developed; however, the application of these theories results in noticeable errors. The analytical solution, which includes the difficult conformal mapping procedure, could be applied for a simple and symmetrical problem only. Therefore, the objectives of this paper are to: 1) develop a surrogate model based on numerical simulated data using SEEPW software to approximately simulate seepage process related to a hydraulic structure, 2) develop and solve a linked simulation-optimization model based on the developed surrogate model to describe the seepage occurring under a concrete gravity dam, in order to obtain optimum and safe design at minimum cost. The result shows that the linked simulation-optimization model provides an efficient and optimum design of concrete gravity dams.Keywords: Artificial neural network, concrete gravity dam, genetic algorithm, seepage analysis.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 13641365 Evaluating Performance of Quality-of-Service Routing in Large Networks
Authors: V. Narasimha Raghavan, M. Venkatesh, T. Peer Meera Labbai, Praveen Dwarakanath Prabhu
Abstract:
The performance and complexity of QoS routing depends on the complex interaction between a large set of parameters. This paper investigated the scaling properties of source-directed link-state routing in large core networks. The simulation results show that the routing algorithm, network topology, and link cost function each have a significant impact on the probability of successfully routing new connections. The experiments confirm and extend the findings of other studies, and also lend new insight designing efficient quality-of-service routing policies in large networks.
Keywords: QoS, Link-State Routing, Dijkstra, Path Selection, Path Computation.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 15641364 Data-organization Before Learning Multi-Entity Bayesian Networks Structure
Authors: H. Bouhamed, A. Rebai, T. Lecroq, M. Jaoua
Abstract:
The objective of our work is to develop a new approach for discovering knowledge from a large mass of data, the result of applying this approach will be an expert system that will serve as diagnostic tools of a phenomenon related to a huge information system. We first recall the general problem of learning Bayesian network structure from data and suggest a solution for optimizing the complexity by using organizational and optimization methods of data. Afterward we proposed a new heuristic of learning a Multi-Entities Bayesian Networks structures. We have applied our approach to biological facts concerning hereditary complex illnesses where the literatures in biology identify the responsible variables for those diseases. Finally we conclude on the limits arched by this work.
Keywords: Data-organization, data-optimization, automatic knowledge discovery, Multi-Entities Bayesian networks, score merging.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 16001363 A PSO-Based Optimum Design of PID Controller for a Linear Brushless DC Motor
Authors: Mehdi Nasri, Hossein Nezamabadi-pour, Malihe Maghfoori
Abstract:
This Paper presents a particle swarm optimization (PSO) method for determining the optimal proportional-integral-derivative (PID) controller parameters, for speed control of a linear brushless DC motor. The proposed approach has superior features, including easy implementation, stable convergence characteristic and good computational efficiency. The brushless DC motor is modelled in Simulink and the PSO algorithm is implemented in MATLAB. Comparing with Genetic Algorithm (GA) and Linear quadratic regulator (LQR) method, the proposed method was more efficient in improving the step response characteristics such as, reducing the steady-states error; rise time, settling time and maximum overshoot in speed control of a linear brushless DC motor.
Keywords: Brushless DC motor, Particle swarm optimization, PID Controller, Optimal control.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 49501362 Comparison of Different Data Acquisition Techniques for Shape Optimization Problems
Authors: Attila Vámosi, Tamás Mankovits, Dávid Huri, Imre Kocsis, Tamás Szabó
Abstract:
Non-linear FEM calculations are indispensable when important technical information like operating performance of a rubber component is desired. For example rubber bumpers built into air-spring structures may undergo large deformations under load, which in itself shows non-linear behavior. The changing contact range between the parts and the incompressibility of the rubber increases this non-linear behavior further. The material characterization of an elastomeric component is also a demanding engineering task. The shape optimization problem of rubber parts led to the study of FEM based calculation processes. This type of problems was posed and investigated by several authors. In this paper the time demand of certain calculation methods are studied and the possibilities of time reduction is presented.
Keywords: Rubber bumper, data acquisition, finite element analysis, support vector regression.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 21301361 Investigation on Feature Extraction and Classification of Medical Images
Authors: P. Gnanasekar, A. Nagappan, S. Sharavanan, O. Saravanan, D. Vinodkumar, T. Elayabharathi, G. Karthik
Abstract:
In this paper we present the deep study about the Bio- Medical Images and tag it with some basic extracting features (e.g. color, pixel value etc). The classification is done by using a nearest neighbor classifier with various distance measures as well as the automatic combination of classifier results. This process selects a subset of relevant features from a group of features of the image. It also helps to acquire better understanding about the image by describing which the important features are. The accuracy can be improved by increasing the number of features selected. Various types of classifications were evolved for the medical images like Support Vector Machine (SVM) which is used for classifying the Bacterial types. Ant Colony Optimization method is used for optimal results. It has high approximation capability and much faster convergence, Texture feature extraction method based on Gabor wavelets etc..Keywords: ACO Ant Colony Optimization, Correlogram, CCM Co-Occurrence Matrix, RTS Rough-Set theory
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 29981360 Optimal Production and Maintenance Policy for a Partially Observable Production System with Stochastic Demand
Authors: Leila Jafari, Viliam Makis
Abstract:
In this paper, the joint optimization of the economic manufacturing quantity (EMQ), safety stock level, and condition-based maintenance (CBM) is presented for a partially observable, deteriorating system subject to random failure. The demand is stochastic and it is described by a Poisson process. The stochastic model is developed and the optimization problem is formulated in the semi-Markov decision process framework. A modification of the policy iteration algorithm is developed to find the optimal policy. A numerical example is presented to compare the optimal policy with the policy considering zero safety stock.Keywords: Condition-based maintenance, economic manufacturing quantity, safety stock, stochastic demand.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 8121359 Non-Smooth Economic Dispatch Solution by Using Enhanced Bat-Inspired Optimization Algorithm
Authors: Farhad Namdari, Reza Sedaghati
Abstract:
Economic dispatch (ED) has been considered to be one of the key functions in electric power system operation which can help to build up effective generating management plans. The practical ED problem has non-smooth cost function with nonlinear constraints which make it difficult to be effectively solved. This paper presents a novel heuristic and efficient optimization approach based on the new Bat algorithm (BA) to solve the practical non-smooth economic dispatch problem. The proposed algorithm easily takes care of different constraints. In addition, two newly introduced modifications method is developed to improve the variety of the bat population when increasing the convergence speed simultaneously. The simulation results obtained by the proposed algorithms are compared with the results obtained using other recently develop methods available in the literature.
Keywords: Non-smooth, economic dispatch, bat-inspired, nonlinear practical constraints, modified bat algorithm.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 20621358 Hybrid Hierarchical Routing Protocol for WSN Lifetime Maximization
Authors: H. Aoudia, Y. Touati, E. H. Teguig, A. Ali Cherif
Abstract:
Conceiving and developing routing protocols for wireless sensor networks requires considerations on constraints such as network lifetime and energy consumption. In this paper, we propose a hybrid hierarchical routing protocol named HHRP combining both clustering mechanism and multipath optimization taking into account residual energy and RSSI measures. HHRP consists of classifying dynamically nodes into clusters where coordinators nodes with extra privileges are able to manipulate messages, aggregate data and ensure transmission between nodes according to TDMA and CDMA schedules. The reconfiguration of the network is carried out dynamically based on a threshold value which is associated with the number of nodes belonging to the smallest cluster. To show the effectiveness of the proposed approach HHRP, a comparative study with LEACH protocol is illustrated in simulations.Keywords: Routing protocols, energy optimization, clustering.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 8901357 Optimization of Technical and Technological Solutions for the Development of Offshore Hydrocarbon Fields in the Kaliningrad Region
Authors: Pavel Shcherban, Viktoria Ivanova, Alexander Neprokin, Vladislav Golovanov
Abstract:
Currently, LLC «Lukoil-Kaliningradmorneft» is implementing a comprehensive program for the development of offshore fields of the Kaliningrad region. This is largely associated with the depletion of the resource base of land in the region, as well as the positive results of geological investigation surrounding the Baltic Sea area and the data on the volume of hydrocarbon recovery from a single offshore field are working on the Kaliningrad region – D-6 «Kravtsovskoye».The article analyzes the main stages of the LLC «Lukoil-Kaliningradmorneft»’s development program for the development of the hydrocarbon resources of the region's shelf and suggests an optimization algorithm that allows managing a multi-criteria process of development of shelf deposits. The algorithm is formed on the basis of the problem of sequential decision making, which is a section of dynamic programming. Application of the algorithm during the consolidation of the initial data, the elaboration of project documentation, the further exploration and development of offshore fields will allow to optimize the complex of technical and technological solutions and increase the economic efficiency of the field development project implemented by LLC «Lukoil-Kaliningradmorneft».
Keywords: Offshore fields of hydrocarbons of the Baltic Sea, Development of offshore oil and gas fields, Optimization of the field development scheme, Solution of multi-criteria tasks in the oil and gas complex, Quality management of technical and technological processes.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 8351356 Process Optimization Regarding Geometrical Variation and Sensitivity Involving Dental Drill- and Implant-Guided Surgeries
Authors: T. Kero, R. Söderberg, M. Andersson, L. Lindkvist
Abstract:
Within dental-guided surgery, there has been a lack of analytical methods for optimizing the treatment of the rehabilitation concepts regarding geometrical variation. The purpose of this study is to find the source of the greatest geometrical variation contributor and sensitivity contributor with the help of virtual variation simulation of a dental drill- and implant-guided surgery process using a methodical approach. It is believed that lower geometrical variation will lead to better patient security and higher quality of dental drill- and implant-guided surgeries. It was found that the origin of the greatest contributor to the most variation, and hence where the foci should be set, in order to minimize geometrical variation was in the assembly category (surgery). This was also the category that was the most sensitive for geometrical variation.Keywords: Variation Simulation, Process Optimization, Guided Surgeries, Dental Prosthesis.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1273