Search results for: hierarchical process control

Authors: Kirill Filianin, Satu-Pia Reinikainen, Tuomo Sainio

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Frequent measurements of product steam quality create a data overload that becomes more and more difficult to handle. In the current study, plant history data with multiple variables was successfully treated by principal component analysis to detect abnormal process behavior, particularly, in copper solvent extraction. The multivariate model is based on the concentration levels of main process metals recorded by the industrial on-stream x-ray fluorescence analyzer. After mean-centering and normalization of concentration data set, two-dimensional multivariate model under principal component analysis algorithm was constructed. Normal operating conditions were defined through control limits that were assigned to squared score values on x-axis and to residual values on y-axis. 80 percent of the data set were taken as the training set and the multivariate model was tested with the remaining 20 percent of data. Model testing showed successful application of control limits to detect abnormal behavior of copper solvent extraction process as early warnings. Compared to the conventional techniques of analyzing one variable at a time, the proposed model allows to detect on-line a process failure using information from all process variables simultaneously. Complex industrial equipment combined with advanced mathematical tools may be used for on-line monitoring both of process streams’ composition and final product quality. Defining normal operating conditions of the process supports reliable decision making in a process control room. Thus, industrial x-ray fluorescence analyzers equipped with integrated data processing toolbox allows more flexibility in copper plant operation. The additional multivariate process control and monitoring procedures are recommended to apply separately for the major components and for the impurities. Principal component analysis may be utilized not only in control of major elements’ content in process streams, but also for continuous monitoring of plant feed. The proposed approach has a potential in on-line instrumentation providing fast, robust and cheap application with automation abilities.

Keywords: abnormal process behavior, failure detection, principal component analysis, solvent extraction

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Authors: M. Helaimi, R. Taleb, D. Benyoucef, B. Belmadani

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This paper presents the design of a polynomial controller with coefficient diagram method (CDM). This controller is used to control the output power of high frequency resonant inverter with LLC tank. One of the most important problems associated with the proposed inverter is achieving ZVS operating during the induction heating process. To overcome this problem, asymmetrical voltage cancellation (AVC) control technique is proposed. The phased look loop (PLL) is used to track the natural frequency of the system. The small signal model of the system with the proposed control is obtained using extending describing function method (EDM). The validity of the proposed control is verified by simulation results.

Keywords: induction heating, AVC control, CDM, PLL, resonant inverter

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Authors: Thien Van Ngo

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The engineering design process is a systematic approach to solving problems. It involves identifying a problem, brainstorming solutions, prototyping and testing solutions, and evaluating the results. The engineering design process can be used to teach students how to solve problems in a creative and innovative way. The research aim of this study was to investigate the effectiveness of using the engineering design process to enhance student learning outcomes in a physics course. A mixed research method was used in this study. The quantitative data were collected using a pretest-posttest control group design. The qualitative data were collected using semi-structured interviews. The sample was 150 first-year students in the Department of Mechanical Engineering Technology at Cao Thang Technical College in Vietnam in the 2022-2023 school year. The quantitative data were collected using a pretest-posttest control group design. The pretest was administered to both groups at the beginning of the study. The posttest was administered to both groups at the end of the study. The qualitative data were collected using semi-structured interviews with a sample of eight students in the experimental group. The interviews were conducted after the posttest. The quantitative data were analyzed using independent sample T-tests. The qualitative data were analyzed using thematic analysis. The quantitative data showed that students in the experimental group, who were taught using the engineering design process, had significantly higher post-test scores on physics problem-solving than students in the control group, who were taught using the conventional method. The qualitative data showed that students in the experimental group were more motivated and engaged in the learning process than students in the control group. Students in the experimental group also reported that they found the engineering design process to be a more effective way of learning physics. The findings of this study suggest that the engineering design process can be an effective way of enhancing student learning outcomes in physics courses. The engineering design process engages students in the learning process and helps them to develop problem-solving skills.

Keywords: engineering design process, problem-solving, learning outcome of physics, students’ physics competencies, deep learning

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Authors: K. Umbleja, M. Ichino, H. Yaguchi

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In this paper, we propose a coloring method for multivariate data visualization by using parallel coordinates based on dissimilarity and tree structure information gathered during hierarchical clustering. The proposed method is an extension for proximity-based coloring that suffers from a few undesired side effects if hierarchical tree structure is not balanced tree. We describe the algorithm by assigning colors based on dissimilarity information, show the application of proposed method on three commonly used datasets, and compare the results with proximity-based coloring. We found our proposed method to be especially beneficial for symbolic data visualization where many individual objects have already been aggregated into a single symbolic object.

Keywords: data visualization, dissimilarity-based coloring, proximity-based coloring, symbolic data

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Authors: Vinayambika S. Bhat, S. Shanmuga Priya, I. Thirunavukkarasu, Shreeranga Bhat

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An attempt has been made to design a decoupling controller for systems with more inputs more outputs with dead time in it. The de-coupler is designed for the chemical process industry 3×3 plant transfer function with dead time. The Quantitative Feedback Theory (QFT) based controller has also been designed here for the 2×2 distillation column transfer function. The developed control techniques were simulated using the MATLAB/Simulink. Also, the stability of the process was analyzed, together with the presence of various perturbations in it. Time domain specifications like setting time along with overshoot and oscillations were analyzed to prove the efficiency of the de-coupler method. The load disturbance rejection was tested along with its performance. The QFT control technique was synthesized based on the stability and performance specifications in the presence of uncertainty in time constant of the plant transfer function through sequential loop shaping technique. Further, the energy efficiency of the distillation column was improved by proper tuning of the controller. A distillation column consumes 3% of the total energy consumption of the world. A suitable control technique is very important from an economic point of view. The real time implementation of the process is under process in our laboratory.

Keywords: distillation, energy, MIMO process, time delay, robust stability

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Authors: Uwe C. Fischer

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Mental health and well-being for employees working in the human service system are getting more and more important given the increasing rate of absenteeism at work. Besides individual capacities, social and community factors seem to be important in the working setting. Starting from a demand resource framework including the classical demand control aspects, social support systems, specific demands and resources of the client work, and work-family conflict were considered in the present study. We state hypothetically, that these factors have a meaningful association with the mental quality of life of employees working in the field of social, educational and health sectors. 1140 employees, working in human service organizations (education, youth care, nursing etc.) were asked for strains and resources at work (selected scales from Salutogenetic Subjective Work Assessment SALSA and own new scales for client work), work-family conflict, and mental quality of life from the German Short Form Health Survey. Considering the complex influences of the variables, we conducted a multiple hierarchical regression analysis. One third of the whole variance of the mental quality of life can be declared by the different variables of the model. When the variables concerning social influences were included in the hierarchical regression, the influence of work related control resource decreased. Excessive workload, work-family conflict, social support by supervisors, co-workers and other persons outside work, as well as strains and resources associated with client work had significant regression coefficients. Conclusions: Social support systems are crucial in the social, educational and health related service sector, regarding the influence on mental well-being. Especially the work-family conflict focuses on the importance of the work-life balance. Also the specific strains and resources of the client work, measured with new constructed scales, showed great impact on mental health. Therefore occupational health promotion should focus more on the social factors within and outside the working place.

Keywords: client interaction, human service system, mental health, social support, work-family conflict

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Authors: Anna Moskaleva

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A prolific body of research in theoretical and experimental linguistics claims that a preference for conceptual or grammatical information in the process of agreement greatly depends on the type of agreement dependency. According to the agreement hierarchy, an anaphoric agreement is more sensitive to semantic or conceptual rather than grammatical information of an antecedent. Furthermore, a higher linear distance between a pronoun and its antecedent is assumed to trigger semantic agreement, yet the hierarchical distance is hardly examined in the research field, and the contribution of each distance factor is unclear. Apart from that, working memory volume is deemed to play a role in maintaining grammatical information during language comprehension. The aim of this study is to observe distance and working memory effects in resolution of anaphora with collective nominals (e.g., team) and to have a closer look at the interaction of the factors. Collective nominals in many languages can have a holistic or distributive meaning and can be addressed by a singular or a plural pronoun, respectively. We investigated linguistic factors of linear and rhetorical (hierarchical) distance and a more general factor of working memory volume in their ability to facilitate the interpretation of the number feature of a collective noun in Russian. An eye-tracking reading experiment on comprehension has been conducted where university students were presented with composed texts, including collective nouns and personal pronouns alluding to them. Different eye-tracking measures were calculated using statistical methods. The results have shown that a significant increase in reading time in the case of a singular pronoun was demonstrated when both distances were high, and no such effect was observed when just one of the distances was high. A decrease in reading time has been obtained with distance in the case of a plural pronoun. The working memory effect was not revealed in the experiment. The resonance of distance factors indicates that not only the linear distance but also the hierarchical distance is of great importance in interpreting pronouns. The experimental findings also suggest that, apart from the agreement hierarchy, the preference for conceptual or grammatical information correlates with the distance between a pronoun and its antecedent.

Keywords: collective nouns, agreement hierarchy, anaphora resolution, eye-tracking, language comprehension

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Authors: Rakesh Kumar Mishra, Tarun Kumar Dan

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Lead-Lag based Internal Model Control method is proposed based on Internal Model Control (IMC) strategy. In this paper, we have designed the Lead-Lag based Internal Model Control for binary distillation column for SISO process (considering only bottom product). The transfer function has been taken from Wood and Berry model. We have find the composition control and disturbance rejection using Lead-Lag based IMC and comparing with the response of simple Internal Model Controller.

Keywords: SISO, lead-lag, internal model control, wood and berry, distillation column

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Authors: Teimuraz Manjapharashvili, Ketevani Manjaparashvili

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Fuzzy logic is a modeling method for complex or ill-defined systems and is a relatively new mathematical approach. Its basis is to consider overlapping cases of parameter values and define operations to manipulate these cases. Fuzzy logic can successfully create operative automatic management or appropriate advisory systems. Fuzzy logic techniques in various operational control technologies have grown rapidly in the last few years. Fuzzy logic is used in many areas of human technological activity. In recent years, fuzzy logic has proven its great potential, especially in the automation of industrial process control, where it allows to form of a control design based on the experience of experts and the results of experiments. The engineering of chemical technological processes uses fuzzy logic in optimal management, and it is also used in process control, including the operational control of continuous cycle chemical industrial, technological processes, where special features appear due to the continuous cycle and correct management acquires special importance. This paper discusses how intelligent systems can be developed, in particular, how fuzzy logic can be used to build knowledge-based expert systems in chemical process engineering. The implemented projects reveal that the use of fuzzy logic in technological process control has already given us better solutions than standard control techniques. Fuzzy logic makes it possible to develop an advisory system for decision-making based on the historical experience of the managing operator and experienced experts. The present paper deals with operational control and management systems of continuous cycle chemical technological processes, including advisory systems. Because of the continuous cycle, many features are introduced in them compared to the operational control of other chemical technological processes. Among them, there is a greater risk of transitioning to emergency mode; the return from emergency mode to normal mode must be done very quickly due to the impossibility of stopping the technological process due to the release of defective products during this period (i.e., receiving a loss), accordingly, due to the need for high qualification of the operator managing the process, etc. For these reasons, operational control systems of continuous cycle chemical technological processes have been specifically discussed, as they are different systems. Special features of such systems in control and management were brought out, which determine the characteristics of the construction of control and management systems. To verify the findings, the development of an advisory decision-making information system for operational control of a lime kiln using fuzzy logic, based on the creation of a relevant expert-targeted knowledge base, was discussed. The control system has been implemented in a real lime production plant with a lime burn kiln, which has shown that suitable and intelligent automation improves operational management, reduces the risks of releasing defective products, and, therefore, reduces costs. The special advisory system was successfully used in the said plant both for the improvement of operational management and, if necessary, for the training of new operators due to the lack of an appropriate training institution.

Keywords: chemical process control systems, continuous cycle industrial technological processes, fuzzy logic, lime kiln

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Authors: Encarnación Álvarez-Verdejo, Raúl Amor-Pulido, Pablo J. Moya-Fernández, Juan F. Muñoz-Rosas, Francisco J. Blanco-Encomienda

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Many companies use the statistical tool named as statistical quality control, and which can have a high cost for the companies interested on these statistical tools. The evaluation of the quality of products and services is an important topic, but the reduction of the cost of the implantation of the statistical quality control also has important benefits for the companies. For this reason, it is important to implement a economic design for the various steps included into the statistical quality control. In this paper, we describe some relevant aspects related to the economic design of a quality control chart for the proportion of defective items. They are very important because the suggested issues can reduce the cost of implementing a quality control chart for the proportion of defective items. Note that the main purpose of this chart is to evaluate and control the proportion of defective items of a production process.

Keywords: proportion, type I error, economic plan, distribution function

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Authors: Magdi M. Nabi, Ding-Li Yu

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This paper presents a neural network based model predictive control (MPC) strategy to control a strongly exothermic reaction with complicated nonlinear kinetics given by Chylla-Haase polymerization reactor that requires a very precise temperature control to maintain product uniformity. In the benchmark scenario, the operation of the reactor must be guaranteed under various disturbing influences, e.g., changing ambient temperatures or impurity of the monomer. Such a process usually controlled by conventional cascade control, it provides a robust operation, but often lacks accuracy concerning the required strict temperature tolerances. The predictive control strategy based on the RBF neural model is applied to solve this problem to achieve set-point tracking of the reactor temperature against disturbances. The result shows that the RBF based model predictive control gives reliable result in the presence of some disturbances and keeps the reactor temperature within a tight tolerance range around the desired reaction temperature.

Keywords: Chylla-Haase reactor, RBF neural network modelling, model predictive control, semi-batch reactors

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Authors: Hyun-Woo Cho

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The monitoring of industrial production quality has to be implemented to alarm early warning for unusual operating conditions. Furthermore, identification of their assignable causes is necessary for a quality control purpose. For such tasks many multivariate statistical techniques have been applied and shown to be quite effective tools. This work presents a process data-based monitoring scheme for production processes. For more reliable results some additional steps of noise filtering and preprocessing are considered. It may lead to enhanced performance by eliminating unwanted variation of the data. The performance evaluation is executed using data sets from test processes. The proposed method is shown to provide reliable quality control results, and thus is more effective in quality monitoring in the example. For practical implementation of the method, an on-line data system must be available to gather historical and on-line data. Recently large amounts of data are collected on-line in most processes and implementation of the current scheme is feasible and does not give additional burdens to users.

Keywords: detection, filtering, monitoring, process data

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Authors: Maryam Kiani

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Non-precious electrocatalysts play a crucial role in the oxygen reduction reaction (ORR) for regenerative fuel cells and rechargeable metal-air batteries. To enhance ORR activity, La (a less active element) is added to modify the activity of Ni. This addition increases the surface contents of Ni2+, N, and S species in LaNi/N-S-C, while still maintaining a substantial specific surface area and hierarchical porosity. Therefore, the additional La is essential for the successful ORR process.In addition, the presence of extra La in the LaNi/N-S-C electrocatalyst enhances the efficiency of charge transfer and improves the surface acid-base characteristics, facilitating the adsorption of oxygen molecules during the ORR process. As a result, this superior and desirable electrocatalyst exhibits significantly enhanced ORR bifunctional activity. In fact, its ORR activity is comparable to that of the 20 wt% Pt/C.

Keywords: fuel cells, batteries, dual-doped carbon black, ORR

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Authors: Akram Khaleghei Ghosheh Balagh, Viliam Makis, Leila Jafari

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In this paper, we present a new maintenance model for a partially observable system subject to two failure modes, namely a catastrophic failure and a failure due to the system degradation. The system is subject to condition monitoring and the degradation process is described by a hidden Markov model. A cost-optimal Bayesian control policy is developed for maintaining the system. The control problem is formulated in the semi-Markov decision process framework. An effective computational algorithm is developed and illustrated by a numerical example.

Keywords: partially observable system, hidden Markov model, competing risks, multivariate Bayesian control

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Authors: Mounir Zekkaoui, Abdelhadi Fennan

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The software evolution control requires a deep understanding of the changes and their impact on different system heterogeneous artifacts. And an understanding of descriptive knowledge of the developed software artifacts is a prerequisite condition for the success of the evolutionary process. The implementation of an evolutionary process is to make changes more or less important to many heterogeneous software artifacts such as source code, analysis and design models, unit testing, XML deployment descriptors, user guides, and others. These changes can be a source of degradation in functional, qualitative or behavioral terms of modified software. Hence the need for a unified approach for extraction and representation of different heterogeneous artifacts in order to ensure a unified and detailed description of heterogeneous software artifacts, exploitable by several software tools and allowing to responsible for the evolution of carry out the reasoning change concerned.

Keywords: heterogeneous software artifacts, software evolution control, unified approach, meta model, software architecture

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Authors: Kwaku Damoah

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This paper presents a methodology and software application (App) designed to empower users in accessing, retrieving, and comparatively exploring data within the hierarchical network framework of the Government Finance Statistics (GFS) system. It explores the ease of navigating the GFS system and identifies the gaps filled by the new methodology and App. The GFS, embodies a complex Hierarchical Network Classification (HNC) structure, encapsulating institutional units, revenues, expenses, assets, liabilities, and economic activities. Navigating this structure demands specialized knowledge, experience, and skill, posing a significant challenge for effective analytics and fiscal policy decision-making. Many professionals encounter difficulties deciphering these classifications, hindering confident utilization of the system. This accessibility barrier obstructs a vast number of professionals, students, policymakers, and the public from leveraging the abundant data and information within the GFS. Leveraging R programming language, Data Science Analytics and Machine Learning, an efficient methodology enabling users to access, navigate, and conduct exploratory comparisons was developed. The machine learning Fiscal Analytics App (FLOWZZ) democratizes access to advanced analytics through its user-friendly interface, breaking down expertise barriers.

Keywords: data science, data wrangling, drilldown analytics, government finance statistics, hierarchical network classification, machine learning, web application.

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Authors: Wiem Daoud Ben Amor, Luis Martínez López, Hela Moalla Frikha

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Most of the multi-criteria group decision making (MCGDM) problems dealing with qualitative criteria require consideration of the large background of expert information. It is common that experts have different degrees of knowledge for giving their alternative assessments according to criteria. So, it seems logical that they use different evaluation scales to express their judgment, i.e., multi granular linguistic scales. In this context, we propose the extension of the classical additive ratio assessment (ARAS) method to the case of a hierarchical linguistics term for managing multi granular linguistic scales in uncertain contexts where uncertainty is modeled by means in linguistic information. The proposed approach is called the extended hierarchical linguistics-ARAS method (ARAS-ELH). Within the ARAS-ELH approach, the DM can diagnose the results (the ranking of the alternatives) in a decomposed style, i.e., not only at one level of the hierarchy but also at the intermediate ones. Also, the developed approach allows a feedback transformation i.e the collective final results of all experts able to be transformed at any level of the extended linguistic hierarchy that each expert has previously used. Therefore, the ARAS-ELH technique makes it easier for decision-makers to understand the results. Finally, An MCGDM case study is given to illustrate the proposed approach.

Keywords: additive ratio assessment, extended hierarchical linguistic, multi-criteria group decision making problems, multi granular linguistic contexts

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Authors: H. M. Côrtes, J. I. Da Silva Filho, M. F. Blos, B. S. Zanon

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In a modern society the factor corresponding to the increase in the level of quality in industrial production demand new techniques of control and machinery automation. In this context, this work presents the implementation of a Paraconsistent-Fuzzy Digital PID controller. The controller is based on the treatment of inconsistencies both in the Paraconsistent Logic and in the Fuzzy Logic. Paraconsistent analysis is performed on the signals applied to the system inputs using concepts from the Paraconsistent Annotated Logic with annotation of two values (PAL2v). The signals resulting from the paraconsistent analysis are two values defined as Dc - Degree of Certainty and Dct - Degree of Contradiction, which receive a treatment according to the Fuzzy Logic theory, and the resulting output of the logic actions is a single value called the crisp value, which is used to control dynamic system. Through an example, it was demonstrated the application of the proposed model. Initially, the Paraconsistent-Fuzzy Digital PID controller was built and tested in an isolated MATLAB environment and then compared to the equivalent Digital PID function of this software for standard step excitation. After this step, a level control plant was modeled to execute the controller function on a physical model, making the tests closer to the actual. For this, the control parameters (proportional, integral and derivative) were determined for the configuration of the conventional Digital PID controller and of the Paraconsistent-Fuzzy Digital PID, and the control meshes in MATLAB were assembled with the respective transfer function of the plant. Finally, the results of the comparison of the level control process between the Paraconsistent-Fuzzy Digital PID controller and the conventional Digital PID controller were presented.

Keywords: fuzzy logic, paraconsistent annotated logic, level control, digital PID

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Authors: Jaewook Ha, Jin-beak Kim, Seongmin Kim

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In order to solve global warming and climate change issues, increased efforts have been devoted towards clean and sustainable energy sources as well as new energy generating devices. Nanogenerator is a device that converts mechanical/thermal energy as produced by small-scale physical change into electricity. Here we propose that nature-leaf surface could be used for preparation of a triboelectric nanogenerator. The nature-leaf surface consists of polydimethylsiloxane microscale pillars and polytetrafluoroethylene nanoparticles. Interaction between the nature-leaf surface and water was studied and the electrical outputs from the motion of single water drop were measured. A 40-μL water drop can generate a peak voltage of 1 V and a peak current of 0.7 μA. This nanogenerator might be used to drive electric devices in the outdoor environments in a sustainable manner.

Keywords: hierarchical surface, lotus-leaf, electrical generator, waterdrop

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Authors: B. Moaveni, S. Morovati

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In recent years, increasing the usage of railway transportations especially in developing countries caused more attention to control systems railway vehicles. Consequently, designing and implementing the modern control systems to improve the operating performance of trains and locomotives become one of the main concerns of researches. Dynamic braking systems is an important safety system which controls the amount of braking torque generated by traction motors, to keep the adhesion coefficient between the wheel-sets and rail road in optimum bound. Adhesion force has an important role to control the braking distance and prevent the wheels from slipping during the braking process. Cascade control structure is one of the best control methods for the wide range of industrial plants in the presence of disturbances and errors. This paper presents cascade control structure based on two forward simple controllers with two feedback loops to control the slip ratio and braking torque. In this structure, the inner loop controls the angular velocity and the outer loop control the longitudinal velocity of the locomotive that its dynamic is slower than the dynamic of angular velocity. This control structure by controlling the torque of DC traction motors, tries to track the desired velocity profile to access the predefined braking distance and to control the slip ratio. Simulation results are employed to show the effectiveness of the introduced methodology in dynamic braking system.

Keywords: cascade control, dynamic braking system, DC traction motors, slip control

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Authors: Luiz F. J. Maia

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This paper presents an approach to fuzzy control, with the use of new pertinence functions, applied in the case of an inverted pendulum. Appropriate definitions of pertinence functions to fuzzy sets make possible the implementation of the controller with only one control rule, resulting in a smooth control surface. The fuzzy control system can be implemented with analog devices, affording a true real-time performance.

Keywords: control surface, fuzzy control, Inverted pendulum, pertinence functions

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Authors: Haibo Zhao, Thomas Andre, Katherine Avery, Alper Kiziltas, Deborah Mielewski

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Silica aerogels were fabricated through a modified rapid supercritical extraction (RSCE) process. The silica aerogels were made using a tetramethyl orthosilicate precursor and then placed in a hot press and brought to the supercritical point of the solvent, ethanol. In order to control the pressure release without a pressure controller, a needle valve was used. The resulting aerogels were then characterized for their physical and chemical properties and compared to silica aerogels created using similar methods. The aerogels fabricated using this modified RSCE method were found to have similar properties to those in other papers using the unmodified RSCE method. Silica aerogel infused glass blanket composite, graphene reinforced silica aerogel composite were also successfully fabricated by this new method. The modified RSCE process and system is a prototype for better gas outflow control with a lower cost of equipment setup. Potentially, this process could be evolved to a continuous low-cost high-volume production process to meet automotive requirements.

Keywords: aerogel, automotive, rapid supercritical extraction process, low cost production

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Authors: Karrar Raoof Kareem Kamoona, Enas Fathi Taher AlHares, Zeynep Isik

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The various disciplines in the construction industry and the co-existence of the people in the various disciplines are what builds well-developed, closely-knit interpersonal skills at various hierarchical levels thus leading to a varied way of leadership. The varied decision making aspects during the lifecycle of a project include: autocratic, participatory and last but not least, free-rein. We can classify some of the decision makers in the construction industry in a hierarchical manner as follows: project executive, project manager, superintendent, office engineer and finally the field engineer. This survey looked at how decisions are made during the construction period by the key stakeholders in the project. From the paper it is evident that the three decision making aspects can be used at different times or at times together in order to bring out the best leadership decision. A blend of different leadership styles should be used to enhance the success rate during the project lifecycle.

Keywords: leadership style, construction, decision-making, built environment

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Authors: Mehmet Halkaci, Ekrem Öztürk, Mevlüt Türköz, H. Selçuk Halkacı

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Hydromechanical deep drawing (HMD) process is an advanced manufacturing process used to form deep parts with only one forming step. In this process, sheet metal blank can be drawn deeper by means of fluid pressure acting on sheet surface in the opposite direction of punch movement. High limiting drawing ratio, good surface quality, less springback characteristic and high dimensional accuracy are some of the advantages of this process. The performance of the HMD process is affected by various process parameters such as fluid pressure, blank holder force, punch-die radius, pre-bulging pressure and height, punch diameter, friction between sheet-die and sheet-punch. The fluid pressure and bank older force are the main loading parameters and affect the formability of HMD process significantly. The punch diameter also influences the limiting drawing ratio (the ratio of initial sheet diameter to punch diameter) of the sheet metal blank. In this research, optimal loading (fluid pressure and blank holder force) profiles were determined for AA 5754-O sheet material through fuzzy control algorithm developed in previous study using LS-DYNA finite element analysis (FEA) software. In the preceding study, the fuzzy control algorithm was developed utilizing geometrical criteria such as thinning and wrinkling. In order to obtain the final desired part with the developed algorithm in terms of the punch diameter requested, the effect of punch diameter, which is the one of the process parameters, on loading profiles was investigated separately using blank thickness of 1 mm. Thus, the practicality of the previously developed fuzzy control algorithm with different punch diameters was clarified. Also, thickness distributions of the sheet metal blank along a curvilinear distance were compared for the FEA in which different punch diameters were used. Consequently, it was found that the use of different punch diameters did not affect the optimal loading profiles too much.

Keywords: Finite Element Analysis (FEA), fuzzy control, hydromechanical deep drawing, optimal loading profiles, punch diameter

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Authors: Darren A. Whitaker, Dan Palmer, Jens Wesholowski, James Flaherty, John Mack, Ahmad B. Albadarin, Gavin Walker

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Traditional mechanosynthesis has been performed by either ball milling or manual grinding. However, neither of these techniques allow the easy application of process control. The temperature may change unpredictably due to friction in the process. Hence the amount of energy transferred to the reactants is intrinsically non-uniform. Recently, it has been shown that the use of Twin-Screw extrusion (TSE) can overcome these limitations. Additionally, TSE enables a platform for continuous synthesis or manufacturing as it is an open-ended process, with feedstocks at one end and product at the other. Several materials including metal-organic frameworks (MOFs), co-crystals and small organic molecules have been produced mechanochemically using TSE. The described advantages of TSE are offset by drawbacks such as increased process complexity (a large number of process parameters) and variation in feedstock flow impacting on product quality. To handle the above-mentioned drawbacks, this study utilizes UV-Vis spectrophotometry (InSpectroX, ColVisTec) as an online tool to gain real-time information about the quality of the product. Additionally, this is combined with real-time process information in an Advanced Process Control system (PharmaMV, Perceptive Engineering) allowing full supervision and control of the TSE process. Further, by characterizing the dynamic behavior of the TSE, a model predictive controller (MPC) can be employed to ensure the process remains under control when perturbed by external disturbances. Two reactions were studied; a Knoevenagel condensation reaction of barbituric acid and vanillin and, the direct amidation of hydroquinone by ammonium acetate to form N-Acetyl-para-aminophenol (APAP) commonly known as paracetamol. Both reactions could be carried out continuously using TSE, nuclear magnetic resonance (NMR) spectroscopy was used to confirm the percentage conversion of starting materials to product. This information was used to construct partial least squares (PLS) calibration models within the PharmaMV development system, which relates the percent conversion to product to the acquired UV-Vis spectrum. Once this was complete, the model was deployed within the PharmaMV Real-Time System to carry out automated optimization experiments to maximize the percentage conversion based on a set of process parameters in a design of experiments (DoE) style methodology. With the optimum set of process parameters established, a series of PRBS process response tests (i.e. Pseudo-Random Binary Sequences) around the optimum were conducted. The resultant dataset was used to build a statistical model and associated MPC. The controller maximizes product quality whilst ensuring the process remains at the optimum even as disturbances such as raw material variability are introduced into the system. To summarize, a combination of online spectral monitoring and advanced process control was used to develop a robust system for optimization and control of two TSE based mechanosynthetic processes.

Keywords: continuous synthesis, pharmaceutical, spectroscopy, advanced process control

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Authors: S.Pandeeswari, Raju Padma

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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: Misganaw Abebe Baye, Ji-Woo Park, Beom-Soo Kang

Abstract:

The product quality of multi-point dieless forming (MDF) is identified to be dependent on the process parameters. Moreover, a certain variation of friction and material properties may have a substantially worse influence on the final product quality. This study proposed on how to compensate the MDF product defects by minimizing the sensitivity of noise parameter variations. This can be attained by reliability-based robust optimization (RRO) technique to obtain the optimal process setting of the controllable parameters. Initially two MDF Finite Element (FE) simulations of AA3003-H14 saddle shape showed a substantial amount of dimpling, wrinkling, and shape error. FE analyses are consequently applied on ABAQUS commercial software to obtain the correlation between the control process setting and noise variation with regard to the product defects. The best prediction models are chosen from the family of metamodels to swap the computational expensive FE simulation. Genetic algorithm (GA) is applied to determine the optimal process settings of the control parameters. Monte Carlo Analysis (MCA) is executed to determine how the noise parameter variation affects the final product quality. Finally, the RRO FE simulation and the experimental result show that the amendment of the control parameters in the final forming process leads to a considerably better-quality product.

Keywords: dimpling, multi-point dieless forming, reliability-based robust optimization, shape error, variation, wrinkling

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Authors: Khaing Yadana Swe, Lillie Dewan

Abstract:

At present, the cascade PID control is widely used to control the super-heating temperature (main steam temperature). As the main steam temperature has the characteristics of large inertia, large time-delay, and time varying, etc., conventional PID control strategy can not achieve good control performance. In order to overcome the bad performance and deficiencies of main steam temperature control system, Model Free Adaptive Control (MFAC) P cascade control system is proposed in this paper. By substituting MFAC in PID of the main control loop of the main steam temperature control, it can overcome time delays, non-linearity, disturbance and time variation.

Keywords: model-free adaptive control, cascade control, adaptive control, PID

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Authors: Harald Lang, Michael Bader, A. Buchroithner

Abstract:

Holistic methods covering the development process as a whole – e.g. systems engineering – have established themselves in product design. However, technical product optimization, representing improvements in efficiency and/or minimization of loss, usually applies to single components of a system. A holistic approach is being defined based on a hierarchical point of view of systems engineering. This is subsequently presented using the example of an electromechanical flywheel energy storage system for automotive applications.

Keywords: design, product development, product optimization, systems engineering

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Authors: Alia Abdul Ghaffar, Tom Richardson

Abstract:

A model reference adaptive control and a fixed gain LQR control were implemented in the height controller of a quadrotor that has parametric uncertainties due to the act of picking up an object of unknown dimension and mass. It is shown that an adaptive control, unlike a fixed gain control, is capable of ensuring a stable tracking performance under such condition, although adaptive control suffers from several limitations. The combination of both adaptive and fixed gain control in the controller architecture results in an enhanced tracking performance in the presence of parametric uncertainties.

Keywords: UAV, quadrotor, robotic arm augmentation, model reference adaptive control, LQR control

Procedia PDF Downloads 464