Search results for: remote control

Authors: Espen Oland

Abstract:

This paper presents a solution to the problem of autonomous rendezvous for spacecraft equipped with one main thruster for translational control and three reaction wheels for rotational control. With fewer actuators than degrees of freedom, this constitutes an underactuated control problem, requiring a coupling between the translational and rotational dynamics to facilitate control. This paper shows how to obtain this coupling, and applies the results to autonomous rendezvous between a follower spacecraft and a leader spacecraft. Additionally, since the thrust is constrained between zero and an upper bound, no negative forces can be generated to slow down the speed of the spacecraft. A combined speed and attitude control logic is therefore created that can be divided into three main phases: 1) The orbital velocity vector is pointed towards the desired position and the thrust is used to obtain the desired speed, 2) during the coasting phase, the attitude is changed to facilitate deceleration using the main thruster, 3) the speed is decreased as the spacecraft reaches its desired position. The results are validated through simulations, showing the capabilities of the proposed approach.

Keywords: attitude control, spacecraft rendezvous, translational control, underactuated rigid body

Procedia PDF Downloads 292

Authors: Endalkachew Abebe Kebede, Bojin Bojinov, Andon Vasilev Andonov, Orhan Dengiz

Abstract:

Remote sensing has a potential application in assessing and monitoring the plants' biophysical properties using the spectral responses of plants and soils within the electromagnetic spectrum. However, only a few reports compare the performance of different remote sensing sensors against in-situ field spectral measurement. The current study assessed the potential applications of open data source satellite images (Sentinel 2 and Landsat 9) in estimating the biophysical properties of the wheat crop on a study farm found in the village of OvchaMogila. A Landsat 9 (30 m resolution) and Sentinel-2 (10 m resolution) satellite images with less than 10% cloud cover have been extracted from the open data sources for the period of December 2021 to April 2022. An Unmanned Aerial Vehicle (UAV) has been used to capture the spectral response of plant leaves. In addition, SpectraVue 710s Leaf Spectrometer was used to measure the spectral response of the crop in April at five different locations within the same field. The ten most common vegetation indices have been selected and calculated based on the reflectance wavelength range of remote sensing tools used. The soil samples have been collected in eight different locations within the farm plot. The different physicochemical properties of the soil (pH, texture, N, P₂O₅, and K₂O) have been analyzed in the laboratory. The finer resolution images from the UAV and the Leaf Spectrometer have been used to validate the satellite images. The performance of different sensors has been compared based on the measured leaf spectral response and the extracted vegetation indices using the five sampling points. A scatter plot with the coefficient of determination (R2) and Root Mean Square Error (RMSE) and the correlation (r) matrix prepared using the corr and heatmap python libraries have been used for comparing the performance of Sentinel 2 and Landsat 9 VIs compared to the drone and SpectraVue 710s spectrophotometer. The soil analysis revealed the study farm plot is slightly alkaline (8.4 to 8.52). The soil texture of the study farm is dominantly Clay and Clay Loam.The vegetation indices (VIs) increased linearly with the growth of the plant. Both the scatter plot and the correlation matrix showed that Sentinel 2 vegetation indices have a relatively better correlation with the vegetation indices of the Buteo dronecompared to the Landsat 9. The Landsat 9 vegetation indices somewhat align better with the leaf spectrometer. Generally, the Sentinel 2 showed a better performance than the Landsat 9. Further study with enough field spectral sampling and repeated UAV imaging is required to improve the quality of the current study.

Keywords: landsat 9, leaf spectrometer, sentinel 2, UAV

Procedia PDF Downloads 107

Authors: Oluwaseun Simon Adekanle, M'hammed Guisser, Elhassane Abdelmounim, Mohamed Aboulfatah

Abstract:

In this paper, modeling and control of a grid connected 660KW Doubly-Fed Induction Generator wind turbine is presented. Stator flux orientation is used to realize active-reactive power decoupling to enable independent control of active and reactive power. The recursive Integral Backstepping technique is used to control generator speed to its optimum value and to obtain unity power factor. The controller is combined with High Gain Observer to estimate the mechanical torque of the machine. The most important advantage of this combination of High Gain Observer and the Integral Backstepping controller is the annulation of static error that may occur due to incertitude between the actual value of a parameter and its estimated value by the controller. Simulation results under Matlab/Simulink show the robustness of this control technique in presence of parameter variation.

Keywords: doubly-fed induction generator, field orientation control, high gain observer, integral backstepping control

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Authors: Oznur Ispir, S. Duygulu

Abstract:

Health institutions are the places where fast and efficient decisions are required and mistakes and uncertainties are not tolerated due to the urgency of the services provided within the body of these institutions. Thus, in those institutions where patient care services are targeted to be provided quality and safety, the nurses attending the decisions, creating the solutions for problems, taking initiative and bearing the responsibility of results in brief having the control over practices are needed. Control over nursing practices is defined as affecting the employment and work environment at the unit level of the institution, perceived freedom for organizing and evaluating nursing practices, the ability to make independent decisions about patient care and accountability for the results of such decisions. This study scrutinizes the concept of control over nursing practices (organizational autonomy), which is frequently confused with other concepts (autonomy) in the literature, by reviewing the literature and making suggestions to improve nurses’ control over nursing practices.

Keywords: control over nursing practice, nurse, nursing, organizational autonomy

Procedia PDF Downloads 266

Authors: C. Asha Poorna, P. G. Vinod, A. R. R. Menon

Abstract:

Currently increasing population and their activities like urbanization and industrialization generating the greatest environmental, issue called Waste. And the major problem in waste management is selection of an appropriate site for waste disposal. The selection of suitable site have constrains like environmental, economical and political considerations. In this paper we discuss the strategies to be followed while selecting a site for decentralized system for solid waste disposal, using Geographic Information System (GIS), the Analytical Hierarchy Process (AHP) and the remote sensing method for Thiruvananthapuram corporation area. It is located on the west coast of India near the extreme south of the mainland. It lies on the shores of Killiyar and Karamana River. Being on the basin the waste managements must be regulated with the water body. The different criteria considered for waste disposal site selection are lithology, surface water, aquifer, groundwater, land use, contours, aspect, elevation, slope, and distance to road, distance from settlement are examined in relation to land fill site selection. Each criterion was identified and weighted by AHP score and mapped using GIS technique and suitable map is prepared by overlay analysis.

Keywords: waste disposal, solid waste management, Geographic Information System (GIS), Analytical Hierarchy Process (AHP)

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Authors: Dhanuj M. Gandikota

Abstract:

Sensor-derived three-dimensional (3D) point clouds of trees are invaluable in remote sensing analysis for the accurate measurement of key structural metrics, bio-inventory values, spatial planning/visualization, and ecological modeling. Machine learning (ML) holds the potential in addressing the restrictive tradeoffs in cost, spatial coverage, resolution, and information gain that exist in current point cloud sensing methods. Terrestrial laser scanning (TLS) remains the highest fidelity source of both canopy and below-canopy structural features, but usage is limited in both coverage and cost, requiring manual deployment to map out large, forested areas. While aerial laser scanning (ALS) remains a reliable avenue of LIDAR active remote sensing, ALS is also cost-restrictive in deployment methods. Space-borne photogrammetry from high-resolution satellite constellations is an avenue of passive remote sensing with promising viability in research for the accurate construction of vegetation 3-D point clouds. It provides both the lowest comparative cost and the largest spatial coverage across remote sensing methods. However, both space-borne photogrammetry and ALS demonstrate technical limitations in the capture of valuable below-canopy point cloud data. Looking to minimize these tradeoffs, we explored a class of powerful ML algorithms called Deep Learning (DL) that show promise in recent research on 3-D point cloud reconstruction and interpolation. Our research details the efficacy of applying these DL techniques to reconstruct accurate below-canopy point clouds from space-borne and aerial remote sensing through learned patterns of tree species fractal symmetry properties and the supplementation of locally sourced bio-inventory metrics. From our dataset, consisting of tree point clouds obtained from TLS, we deconstructed the point clouds of each tree into those that would be obtained through ALS and satellite photogrammetry of varying resolutions. We fed this ALS/satellite point cloud dataset, along with the simulated local bio-inventory metrics, into the DL point cloud reconstruction architectures to generate the full 3-D tree point clouds (the truth values are denoted by the full TLS tree point clouds containing the below-canopy information). Point cloud reconstruction accuracy was validated both through the measurement of error from the original TLS point clouds as well as the error of extraction of key structural metrics, such as crown base height, diameter above root crown, and leaf/wood volume. The results of this research additionally demonstrate the supplemental performance gain of using minimum locally sourced bio-inventory metric information as an input in ML systems to reach specified accuracy thresholds of tree point cloud reconstruction. This research provides insight into methods for the rapid, cost-effective, and accurate construction of below-canopy tree 3-D point clouds, as well as the supported potential of ML and DL to learn complex, unmodeled patterns of fractal tree growth symmetry.

Keywords: deep learning, machine learning, satellite, photogrammetry, aerial laser scanning, terrestrial laser scanning, point cloud, fractal symmetry

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Authors: Maria Ahmadnezhad, Seyedgharani Ghoreishi ‎

Abstract:

Electrohydraulic servo system have been used in industry in a wide ‎number of applications. Its ‎dynamics are highly nonlinear and also ‎have large extent of model uncertainties and external ‎disturbances. ‎In this thesis, a robust back-stepping control (RBSC) scheme is ‎proposed to overcome ‎the problem of disturbances and system ‎uncertainties effectively and to improve the set-point ‎performance ‎of EHS systems. In order to implement the proposed control ‎scheme, the system ‎uncertainties in EHS systems are considered as ‎total leakage coefficient and effective oil volume. In ‎addition, in ‎order to obtain the virtual controls for stabilizing system, the ‎update rule for the ‎system uncertainty term is induced by the ‎Lyapunov control function (LCF). To verify the ‎performance and ‎robustness of the proposed control system, computer simulation of ‎the ‎proposed control system using Matlab/Simulink Software is ‎executed. From the computer ‎simulation, it was found that the ‎RBSC system produces the desired set-point performance and ‎has ‎robustness to the disturbances and system uncertainties of ‎EHS systems.‎

Keywords: electro hydraulic servo system, back-stepping control, robust back-‎stepping control, Lyapunov redesign‎

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Authors: Auwal Mustapha Imam

Abstract:

The aim of the energy management system is to monitor and control utilization, access, optimize and manage energy availability. This can be realized through real-time analyses and energy sources and loads data control in a predictive way. Smart-home monitoring and control provide convenience and cost savings by controlling appliances, lights, thermostats and other loads. There may be different categories of loads in the various homes, and the homeowner may wish to control access to solar-generated energy to protect the storage from draining completely. Controlling the power system operation by managing the converter output power and controlling how it feeds the appliances will satisfy the residential load demand. The Internet of Things (IoT) provides an attractive technological platform to connect the two and make home automation and domestic energy utilization easier and more attractive. This paper presents the use of IoT-based control topology to monitor and control power distribution and consumption by DC loads connected to single-input multiple outputs (SIMO) DC-DC converter, thereby reducing leakages, enhancing performance and reducing human efforts. A SIMO converter was first developed and integrated with the IoT/Raspberry Pi control topology, which enables the user to monitor and control power scheduling and load forecasting via an Android app.

Keywords: flyback, converter, DC-DC, photovoltaic, SIMO

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Authors: Badr M. Alshammari, A. Rabeh, A. K. Mohamed

Abstract:

This paper presents the modeling and the control of a grid-connected photovoltaic system (PVS). Firstly, the MPPT control of the PVS and its associated DC/DC converter has been analyzed in order to extract the maximum of available power. Secondly, the control system of the grid side converter (GSC) which is a three-phase voltage source inverter (VSI) has been presented. A special attention has been paid to the control algorithms of the GSC converter during grid voltages imbalances. Especially, three different control objectives are to achieve; the mitigation of the grid imbalance adverse effects, at the point of common coupling (PCC), on the injected currents, the elimination of double frequency oscillations in active power flow, and the elimination of double frequency oscillations in reactive power flow. Simulation results of two control strategies have been performed via MATLAB software in order to demonstrate the particularities of each control strategy according to power quality standards.

Keywords: renewable energies, photovoltaic systems, dc link, voltage source inverter, space vector SVPWM, unbalanced voltage dips, symmetrical components

Procedia PDF Downloads 377

Authors: A. Moualdia, D. J. Boudana, O. Bouchhida, A. Medjber

Abstract:

Wind energy has many advantages, it does not pollute and it is an inexhaustible source. However, the cost of this energy is still too high to compete with traditional fossil fuels, especially on sites less windy. The performance of a wind turbine depends on three parameters: the power of wind, the power curve of the turbine and the generator's ability to respond to wind fluctuations. This paper presents a control chain conversion based on a double-fed asynchronous machine and flow-oriented. The supply system comprises of two identical converters, one connected to the rotor and the other one connected to the network via a filter. The architecture of the device is up by three commands are necessary for the operation of the turbine control extraction of maximum power of the wind to control itself (MPPT) control of the rotor side converter controlling the electromagnetic torque and stator reactive power and control of the grid side converter by controlling the DC bus voltage and active power and reactive power exchanged with the network. The proposed control has been validated in both modes of operation of the three-bladed wind 7.5 kW, using Matlab/Simulink. The results of simulation control technology study provide good dynamic performance and static.

Keywords: D.F.I.G, variable wind speed, hypersynchrone, energy quality, hyposynchrone

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Authors: Jasper Kevin C. Dionisio, Denise Mae M. Unsay

Abstract:

In a manufacturing firm, controlling the process ensures that optimum efficiency, productivity, and quality in an organization are achieved. An operation with no standardized procedure yields a poor productivity, inefficiency, and an out of control process. This study focuses on controlling the small intestine processing of a chicken dressing plant through the use of Statistical Process Control (SPC). Since the operation does not employ a standard procedure and does not have an established standard time, the process through the assessment of the observed time of the overall operation of small intestine processing, through the use of X-Bar R Control Chart, is found to be out of control. In the solution of this problem, the researchers conduct a motion and time study aiming to establish a standard procedure for the operation. The normal operator was picked through the use of Westinghouse Rating System. Instead of utilizing the traditional motion and time study, the researchers used the X-Bar R Control Chart in determining the process average of the process that is used for establishing the standard time. The observed time of the normal operator was noted and plotted to the X-Bar R Control Chart. Out of control points that are due to assignable cause were removed and the process average, or the average time the normal operator conducted the process, which was already in control and free form any outliers, was obtained. The process average was then used in determining the standard time of small intestine processing. As a recommendation, the researchers suggest the implementation of the standard time established which is with consonance to the standard procedure which was adopted from the normal operator. With that recommendation, the whole operation will induce a 45.54 % increase in their productivity.

Keywords: motion and time study, process controlling, statistical process control, X-Bar R Control chart

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Authors: Tomoaki Hashimoto

Abstract:

Recently, optimal control problems subject to probabilistic constraints have attracted much attention in many research field. Although probabilistic constraints are generally intractable in optimization problems, several methods haven been proposed to deal with probabilistic constraints. In most methods, probabilistic constraints are transformed to deterministic constraints that are tractable in optimization problems. This paper examines a method for transforming probabilistic constraints into deterministic constraints for a class of probabilistic constrained optimal control problems.

Keywords: optimal control, stochastic systems, discrete-time systems, probabilistic constraints

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Authors: Joshua Adan Valdez, Shawn Gallaher

Abstract:

Global climate change has impacted atmospheric temperatures contributing to rising sea levels, decreasing sea ice, and increased freshening of high latitude oceans. This freshening has contributed to increased stratification inhibiting local mixing and nutrient transport, modifying regional circulations in polar oceans. In recent years, the Western Arctic has seen an increase in freshwater volume at an average rate of 397+-116km3/year across the Beaufort Gyre. The majority of the freshwater volume resides in the Beaufort Gyre surface lens driven by anticyclonic wind forcing, sea ice melt, and Arctic river runoff, and is typically defined as water fresher than 34.8. The near-isothermal nature of Arctic seawater and non-linearities in the equation of state for near-freezing waters result in a salinity-driven pycnocline as opposed to the temperature-driven density structure seen in the lower latitudes. In this study, we investigate the relationship between freshwater content and dynamic ocean topography (DOT). In situ measurements of freshwater content are useful in providing information on the freshening rate of the Beaufort Gyre; however, their collection is costly and time-consuming. Utilizing NASA’s ICESat-2’s DOT remote sensing capabilities and Air Expendable CTD (AXCTD) data from the Seasonal Ice Zone Reconnaissance Surveys (SIZRS), a linear regression model between DOT and freshwater content is determined along the 150° west meridian. Freshwater content is calculated by integrating the volume of water between the surface and a depth with a reference salinity of ~34.8. Using this model, we compare interannual variability in freshwater content within the gyre, which could provide a future predictive capability of freshwater volume changes in the Beaufort-Chukchi Sea using non-in situ methods. Successful employment of the ICESat-2’s DOT approximation of freshwater content could potentially demonstrate the value of remote sensing tools to reduce reliance on field deployment platforms to characterize physical ocean properties.

Keywords: Cryosphere, remote sensing, Arctic oceanography, climate modeling, Ekman transport

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Authors: Mamyrbek A. Beisenbi, Nurgul M. Kissikova, Saltanat E. Beisembina, Salamat T. Suleimenova, Samal A. Kaliyeva

Abstract:

The paper proposes a method for constructing a self-organizing control system for unstable and deterministic chaotic processes in the class of catastrophe “hyperbolic umbilic” for objects with m-inputs and n-outputs. The self-organizing control system is investigated by the universal gradient-velocity method of Lyapunov vector functions. The conditions for self-organization of the control system in the class of catastrophes “hyperbolic umbilic” are shown in the form of a system of algebraic inequalities that characterize the aperiodic robust stability in the stationary states of the system.

Keywords: gradient-velocity method of Lyapunov vector-functions, hyperbolic umbilic, self-organizing control system, stability

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Authors: S.Pandeeswari, Raju Padma

Abstract:

In this paper a new solution to implement and control single-stage electronic ballast based on the integration of a buck-boost power factor correction stage and a half bridge resonant inverter is presented. The control signals are obtained using the inverter resonant current by means of a saturable transformer. Core saturation is used to control the required dead time between the control pulses on both switches. The turn-on time of one of the inverter switches is controlled to provide proper cathode preheating during the lamp ignition process. No special integrated circuits are required to control the ballast and the total number of components is minimized. Analysis and basic design of phase cut dimmer.

Keywords: MOSFET dimmer, PIC 16F877A, voltage regulator, bridge rectifier

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Authors: Mihai Caramihai, Dan Vasilescu

Abstract:

The main research objective of the experimental bioprocess analyzed in this paper was to obtain large biomass quantities. The bioprocess is performed in 100 L Bioengineering bioreactor with 42 L cultivation medium made of peptone, meat extract and sodium chloride. The reactor was equipped with pH, temperature, dissolved oxygen, and agitation controllers. The operating parameters were 37 oC, 1.2 atm, 250 rpm and air flow rate of 15 L/min. The main objective of this paper is to present a case study to demonstrate that intelligent control, describing the complexity of the biological process in a qualitative and subjective manner as perceived by human operator, is an efficient control strategy for this kind of bioprocesses. In order to simulate the bioprocess evolution, an intelligent control structure, based on fuzzy logic has been designed. The specific objective is to present a fuzzy control approach, based on human expert’ rules vs. a modeling approach of the cells growth based on bioprocess experimental data. The kinetic modeling may represent only a small number of bioprocesses for overall biosystem behavior while fuzzy control system (FCS) can manipulate incomplete and uncertain information about the process assuring high control performance and provides an alternative solution to non-linear control as it is closer to the real world. Due to the high degree of non-linearity and time variance of bioprocesses, the need of control mechanism arises. BIOSIM, an original developed software package, implements such a control structure. The simulation study has showed that the fuzzy technique is quite appropriate for this non-linear, time-varying system vs. the classical control method based on a priori model.

Keywords: intelligent, control, fuzzy model, bioprocess optimization

Procedia PDF Downloads 326

Authors: Ahmad Sharif Ahmadi, Yoshitaka Kajita

Abstract:

With massive population expansion and fast economic development in last decade, urban land has increasingly expanded and formed high informal development territory in Kabul city. This paper investigates integrated urbanization trends in Kabul city since the formation of the basic structure of the present city using GIS and remote sensing. This study explores the spatial and temporal difference of urban land expansion and land use categories among different time intervals, 1964-1978 and 1978-2008 from 1964 to 2008 in Kabul city. Furthermore, the goal of this paper is to understand the extent of urban land expansion and the factors driving urban land expansion in Kabul city. Many factors like population expansion, the return of refugees from neighboring countries and significant economic growth of the city affected urban land expansion. Across all the study area urban land expansion rate, population expansion rate and economic growth rate have been compared to analyze the relationship of driving forces with urban land expansion. Based on urban land change data detected by interpreting land use maps, it was found that in the entire study area the urban territory has been expanded by 14 times between 1964 and 2008.

Keywords: GIS, Kabul city, land use, urban land expansion, urbanization

Procedia PDF Downloads 339

Authors: Walid Fantazi

Abstract:

The development of sensor technology (such as microelectromechanical systems (MEMS), wireless communications, embedded systems, distributed processing and wireless sensor applications) has contributed to a broad range of WSN applications which are capable of collecting a large amount of spatiotemporal data in real time. These systems require real-time data processing to manage storage in real time and query the data they process. In order to cover these needs, we propose in this paper a Snapshot spatiotemporal data model based on object-oriented concepts. This model allows saving storing and reducing data redundancy which makes it easier to execute spatiotemporal queries and save analyzes time. Further, to ensure the robustness of the system as well as the elimination of congestion from the main access memory we propose a spatiotemporal indexing technique in RAM called Captree *. As a result, we offer an RIA (Rich Internet Application) -based SOA application architecture which allows the remote monitoring and control.

Keywords: WSN, indexing data, SOA, RIA, geographic information system

Procedia PDF Downloads 253

Authors: Maria Ahmadnezhad, Mohammad Reza Soltanpour

Abstract:

Electrohydraulic servo systems have been used in industry in a wide number of applications. Its dynamics ‎are highly nonlinear and also have large extent of model uncertainties and external disturbances. In this ‎thesis, a robust back-stepping control (RBSC) scheme is proposed to overcome the problem of ‎disturbances and system uncertainties effectively and to improve the tracking performance of EHS ‎systems. In order to implement the proposed control scheme, the system uncertainties in EHS systems ‎are considered as total leakage coefficient and effective oil volume. In addition, in order to obtain the ‎virtual controls for stabilizing system, the update rule for the system uncertainty term is induced by the ‎Lyapunov control function (LCF). To verify the performance and robustness of the proposed control ‎system, computer simulation of the proposed control system using Matlab/Simulink Software is ‎executed. From the computer simulation, it was found that the RBSC system produces the desired ‎tracking performance and has robustness to the disturbances and system uncertainties of EHS systems.‎

Keywords: electro hydraulic servo system, back-stepping control, robust back-stepping control, Lyapunov redesign

Procedia PDF Downloads 295

Authors: Berhanu Keno Terfa

Abstract:

To understand the consequences of urbanization, accurate, and long-term representation of urban dynamics is essential. Remote sensing data from various multi-temporal satellite images viz., TM (1987), TM (1995), ETM+ (2005) and OLI (2017) were used. An integrated method, landscape metrics, built-up density, and urban growth type analysis were employed to analyze the pattern, process, and overall growth status in the city. The result showed that the built-up area had increased by 541.3% between 1987 and 2017, at an average annual increment of 8.9%. The area of urban expansion in a city has tripled during the 2005-2017 period as compared to 187- 1995. The major growth took place in the east and southeast directions during 1987–1995 period, whereas predominant built-up development was observed in south and southeast direction during 1995–2017 period. The analysis using landscape metrics and urban typologies showed that Hawassa experienced a fragmented and irregular spatiotemporal urban growth patterns, mostly by extension, suggesting a strong tendency towards sprawl in the past three decades.

Keywords: Hawassa, spatial patterns, remote sensing, multi-temporal, urban sprawl

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Authors: Ali Akbar Heydari

Abstract:

Control charts are an important tool of statistical quality control. Thesecharts are used to detect and eliminate unwanted special causes of variation that occurred during aperiod of time. The design and operation of control charts require the determination of three design parameters: the sample size (n), the sampling interval (h), and the width coefficient of control limits (k). Thevariable parameters (VP) x-bar controlchart is the x-barchart in which all the design parameters vary between twovalues. These values are a function of the most recent process information. In fact, in the VP x-bar chart, the position of each sample point on the chart establishes the size of the next sample and the timeof its sampling. The synthetic x-barcontrol chartwhich integrates the x-bar chart and the conforming run length (CRL) chart, provides significant improvement in terms of detection power over the basic x-bar chart for all levels of mean shifts. In this paper, we introduce the syntheticVP x-bar control chart for monitoring changes in the process mean. To determine the design parameters, we used a statistical design based on the minimum out of control average run length (ARL) criteria. The optimal chart parameters of the proposed chart are obtained using the Markov chain approach. A numerical example is also done to show the performance of the proposed chart and comparing it with the other control charts. The results show that our proposed syntheticVP x-bar controlchart perform better than the synthetic x-bar controlchart for all shift parameter values. Also, the syntheticVP x-bar controlchart perform better than the VP x-bar control chart for the moderate or large shift parameter values.

Keywords: control chart, markov chain approach, statistical design, synthetic, variable parameter

Procedia PDF Downloads 154

Authors: Ali J. Ghandour, Houssam A. Krayem, Abedelkarim A. Jezzini

Abstract:

High-resolution satellite images and remote sensing can provide global information in a fast way compared to traditional methods of data collection. Under such high resolution, a road is not a thin line anymore. Objects such as cars and trees are easily identifiable. Automatic vehicles enumeration can be considered one of the most important applications in traffic management. In this paper, autonomous vehicle detection and classification approach in highway environment is proposed. This approach consists mainly of three stages: (i) first, a set of preprocessing operations are applied including soil, vegetation, water suppression. (ii) Then, road networks detection and delineation is implemented using built-up area index, followed by several morphological operations. This step plays an important role in increasing the overall detection accuracy since vehicles candidates are objects contained within the road networks only. (iii) Multi-level Otsu segmentation is implemented in the last stage, resulting in vehicle detection and classification, where detected vehicles are classified into cars and trucks. Accuracy assessment analysis is conducted over different study areas to show the great efficiency of the proposed method, especially in highway environment.

Keywords: remote sensing, object identification, vehicle and road extraction, vehicle and road features-based classification

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Authors: Saad Algharib, Jay Lee

Abstract:

Urbanization is a complex phenomenon that occurs during the city’s development from one form to another. In other words, it is the process when the activities in the land use/land cover change from rural to urban. Since the oil exploration, Kuwait City has been growing rapidly due to its urbanization and population growth by both natural growth and inward immigration. The main objective of this study is to detect changes in urban land use/land cover and to examine the changing spatial patterns of urban growth in and around Kuwait City between 1989 and 2001. In addition, this study also evaluates the spatial patterns of the changes detected and how they can be related to the spatial configuration of the city. Recently, the use of remote sensing and geographic information systems became very useful and important tools in urban studies because of the integration of them can allow and provide the analysts and planners to detect, monitor and analyze the urban growth in a region effectively. Moreover, both planners and users can predict the trends of the growth in urban areas in the future with remotely sensed and GIS data because they can be effectively updated with required precision levels. In order to identify the new urban areas between 1989 and 2001, the study uses satellite images of the study area and remote sensing technology for classifying these images. Unsupervised classification method was applied to classify images to land use and land cover data layers. After finishing the unsupervised classification method, GIS overlay function was applied to the classified images for detecting the locations and patterns of the new urban areas that developed during the study period. GIS was also utilized to evaluate the distribution of the spatial patterns. For example, Moran’s index was applied for all data inputs to examine the urban growth distribution. Furthermore, this study assesses if the spatial patterns and process of these changes take place in a random fashion or with certain identifiable trends. During the study period, the result of this study indicates that the urban growth has occurred and expanded 10% from 32.4% in 1989 to 42.4% in 2001. Also, the results revealed that the largest increase of the urban area occurred between the major highways after the forth ring road from the center of Kuwait City. Moreover, the spatial distribution of urban growth occurred in cluster manners.

Keywords: geographic information systems, remote sensing, urbanization, urban growth

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Authors: Rituparna Nath, Shawn J. Marshall

Abstract:

Glaciers are one of the main sensitive climatic indicators, as they respond strongly to small climatic shifts. We develop a flow line model of glacier dynamics to simulate the past and future extent of glaciers in the Canadian Rocky Mountains, with the aim of coupling this model within larger scale regional climate models of glacier response to climate change. This paper will focus on glacier-climate modeling and reconstructions of glacier volume from the Little Ice Age (LIA) to present for Athabasca Glacier, Alberta, Canada. Glacier thickness, volume and mass change will be constructed using flow line modelling and examination of different climate scenarios that are able to give good reconstructions of LIA ice extent. With the availability of SPOT 5 imagery, Digital elevation models and GIS Arc Hydro tool, ice catchment properties-glacier width and LIA moraines have been extracted using automated procedures. Simulation of glacier mass change will inform estimates of meltwater run off over the historical period and model calibration from the LIA reconstruction will aid in future projections of the effects of climate change on glacier recession. Furthermore, the model developed will be effective for further future studies with ensembles of glaciers.

Keywords: flow line modeling, Athabasca Glacier, glacier mass balance, Remote Sensing, Arc hydro tool, little ice age

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Authors: Atakan Aral Ormancı, Tuğçe Arslantaş, Murat Özcü

Abstract:

This study presents the design and implementation of an experimental chassis-level system for various control applications. Specifically, the height level of the chassis is controlled using proportional integrated derivative, fuzzy logic, and deep learning control methods. Real-time data obtained from height and pressure sensors installed in a 6x2 truck chassis, in combination with pulse-width modulation signal values, are utilized during the tests. A prototype pneumatic system of a 6x2 truck is added to the setup, which enables the Smart Pneumatic Actuators to function as if they were in a real-world setting. To obtain real-time signal data from height sensors, an Arduino Nano is utilized, while a Raspberry Pi processes the data using Matlab/Simulink and provides the correct output signals to control the Smart Pneumatic Actuator in the truck chassis. The objective of this research is to optimize the time it takes for the chassis to level down and up under various loads. To achieve this, proportional integrated derivative control, fuzzy logic control, and deep learning techniques are applied to the system. The results show that the deep learning method is superior in optimizing time for a non-linear system. Fuzzy logic control with a triangular membership function as the rule base achieves better outcomes than proportional integrated derivative control. Traditional proportional integrated derivative control improves the time it takes to level the chassis down and up compared to an uncontrolled system. The findings highlight the superiority of deep learning techniques in optimizing the time for a non-linear system, and the potential of fuzzy logic control. The proposed approach and the experimental results provide a valuable contribution to the field of control, automation, and systems engineering.

Keywords: automotive, chassis level control, control systems, pneumatic system control

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Authors: Francys Souza, Alberto Ohashi, Dorival Leao

Abstract:

We present a general solution for finding the ε-optimal controls for non-Markovian stochastic systems as stochastic differential equations driven by Brownian motion, which is a problem recognized as a difficult solution. The contribution appears in the development of mathematical tools to deal with modeling and control of non-Markovian systems, whose applicability in different areas is well known. The methodology used consists to discretize the problem through a random discretization. In this way, we transform an infinite dimensional problem in a finite dimensional, thereafter we use measurable selection arguments, to find a control on an explicit form for the discretized problem. Then, we prove the control found for the discretized problem is a ε-optimal control for the original problem. Our theory provides a concrete description of a rather general class, among the principals, we can highlight financial problems such as portfolio control, hedging, super-hedging, pairs-trading and others. Therefore, our main contribution is the development of a tool to explicitly the ε-optimal control for non-Markovian stochastic systems. The pathwise analysis was made through a random discretization jointly with measurable selection arguments, has provided us with a structure to transform an infinite dimensional problem into a finite dimensional. The theory is applied to stochastic control problems based on path-dependent stochastic differential equations, where both drift and diffusion components are controlled. We are able to explicitly show optimal control with our method.

Keywords: dynamic programming equation, optimal control, stochastic control, stochastic differential equation

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Authors: Xudong Guan, Ainong Li, Gaohuan Liu, Chong Huang, Wei Zhao

Abstract:

Due to the low spatial resolution of MODIS data, the accuracy of small-area plaque extraction with a high degree of landscape fragmentation is greatly limited. To this end, the study combines Landsat data with higher spatial resolution and MODIS data with higher temporal resolution for decision-level fusion. Considering the importance of the land heterogeneity factor in the fusion process, it is superimposed with the weighting factor, which is to linearly weight the Landsat classification result and the MOIDS classification result. Three levels were used to complete the process of data fusion, that is the pixel of MODIS data, the pixel of Landsat data, and objects level that connect between these two levels. The multilevel decision fusion scheme was tested in two sites of the lower Mekong basin. We put forth a comparison test, and it was proved that the classification accuracy was improved compared with the single data source classification results in terms of the overall accuracy. The method was also compared with the two-level combination results and a weighted sum decision rule-based approach. The decision fusion scheme is extensible to other multi-resolution data decision fusion applications.

Keywords: image classification, decision fusion, multi-temporal, remote sensing

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Authors: L. Benaaouinate, M. Khafallah, A. Martinez, A. Mesbahi, T. Bouragba

Abstract:

This paper concerns with the modeling, simulation, and emulation of a wind turbine emulator for standalone wind energy conversion systems. By using emulation system, we aim to reproduce the dynamic behavior of the wind turbine torque on the generator shaft: it provides the testing facilities to optimize generator control strategies in a controlled environment, without reliance on natural resources. The aerodynamic, mechanical, electrical models have been detailed as well as the control of pitch angle using Fuzzy Logic for horizontal axis wind turbines. The wind turbine emulator consists mainly of an induction motor with AC power drive with torque control. The control of the induction motor and the mathematical models of the wind turbine are designed with MATLAB/Simulink environment. The simulation results confirm the effectiveness of the induction motor control system and the functionality of the wind turbine emulator for providing all necessary parameters of the wind turbine system such as wind speed, output torque, power coefficient and tip speed ratio. The findings are of direct practical relevance.

Keywords: electrical generator, induction motor drive, modeling, pitch angle control, real time control, renewable energy, wind turbine, wind turbine emulator

Procedia PDF Downloads 234

Authors: Hung-Jiun Chi, Cheng-En Tsai, Jia-Ying Tu

Abstract:

Semi-active control of Magnetorheological (MR) dampers for vibration reduction of structural systems has received considerable attention in civil and earthquake engineering, because the effective stiffness and damping properties of MR fluid can change in a very short time in reaction to external loading, requiring only a low level of power. However, the inherent nonlinear dynamics of hysteresis raise challenges in the modeling and control processes. In order to control the MR damper, an innovative Duffing-like equation is proposed to approximate the hysteresis dynamics in a deterministic and systematic manner than previously has been possible. Then, the model-reference adaptive control technique based on the Duffing-like model and the Lyapunov method is discussed. Parameter identification work with experimental data is presented to show the effectiveness of the Duffing-like model. In addition, simulation results show that the resulting adaptive gains enable the MR damper force to track the desired response of the reference model satisfactorily, verifying the effectiveness of the proposed modeling and control techniques.

Keywords: magnetorheological damper, duffing equation, model-reference adaptive control, Lyapunov function, hysteresis

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Authors: M. P. Nanda Kumar, K. Dheeraj

Abstract:

The design of a feedback controller, so as to minimize a given performance criterion, for a general non-linear dynamical system is difficult; if not impossible. But for a large class of non-linear dynamical systems, the open loop control that minimizes a performance criterion can be obtained using calculus of variations and Pontryagin’s minimum principle. In this paper, the open loop optimal trajectories, that minimizes a given performance measure, is used to train the neural network whose inputs are state variables of non-linear dynamical systems and the open loop optimal control as the desired output. This trained neural network is used as the feedback controller. In other words, attempts are made here to solve the “inverse optimal control problem” by using the state and control trajectories that are optimal in an open loop sense.

Keywords: inverse optimal control, radial basis function, neural network, controller design

Procedia PDF Downloads 553