1,720,958 research outputs found
Highly nonlinear control of a solar thermal power plant using soft computing fuzzy tuning techniques
No full textSociety is experiencing massive growth of global industrialised populations, which is putting
increasing pressure on western governments to pursue more persuasive means to maintain and increase
their share of the world’s diminishing fossil fuel reserves. To combat this, there is a growing body of
enlightened researchers who are directing their abilities towards the development of alternative and
preferably renewable energy types of supply systems. Many of these real world systems exhibit varying
degrees of non-linearity. An example of this is the significant variations in the dynamic characteristics of
a distributed collector field within a solar thermal power plant. Here a Sugeno-type fuzzy incremental
controller was tuned using an ANFIS (Adaptive Neural Fuzzy Inference System) to optimise the fuzzy
controller’s pre-clustered input membership functions, while a multiobjective genetic algorithm with an
enhanced decision support system was used to fine tune the parameters of its first order output
membership functions. The resulting solution choice produced an incremental fuzzy controller which was
used to successfully control the plant exclusively in its high nonlinear regions, i.e., where the oil flow fell
below 5 litres per second. This allowed the plant to function in environments where local solar radiation
conditions have always been regarded as marginal. A feedforward term was also used to control plant
disturbances caused by solar irradiation, mirror reflectivity etc
Hybrid control and evolutionary decision support within a sustainable environment
No full textDue to the increased global demand for energy, and the potential dangersof relying too heavily on our fossil fuel reserves, more and more research is being directed towards alternative, and preferably reusable or sustainable forms of energy supply. Many of these real world systems have operating regions that exhibit varying degrees of non-linearity. An example of this are the significant variations in the dynamic characteristics of a distributed collector field within a solar power plant. Here a control scheme employs a fuzzy PI controller, with feedforward, for the highly nonlinear part of the operating regime and gain scheduled controller for the more linear part of the operating envelope. In order to satisfy performance characteristics for the plant at different points in the operating regime, a multiobjective genetic algorithm with enhanced decision support system, is used to design the parameters of the fuzzy controller
Optimization of a renewable energy supply system using hard and soft computational control methodologies: a hybrid approach
No full textAs humanity becomes increasingly aware of the urgent need to re-address the delicate balance of nature, and as the Earth moves closer towards the natural global warming maximum of its current interglaciation, the reluctance of its decision makers to use the Earth’s diminishing supplies of fossil fuels in the traditional way is becoming more evident. To meet some of these changing objectives, research is gaining momentum into developing new forms of energy supply systems that are globally accessible, globally sustainable, and whose contribution to the current warming trends of our planet is negligible.Many of these real world energy systems have operating regions that exhibit varying degrees of non-linearity. An example of this is the significant variations in the dynamic characteristics of a distributed, solar-concentrating, parabolic collector field within a pilot solar thermal power plant situated in the Tabernas Desert, Almería, Spain.Here a hybrid controller was implemented, using a gain-scheduled controller with feed¬forward, to control the more linear operating regimes, while the natural task-orientated strengths of a fuzzy PI incremental controller were utilized to control the highly nonlinear operating region of the plant, i.e. below 5 litres per second. Removing the step-orientated nature of the problem from the fuzzy controller allows Multi-Objective Genetic Algorithm (MOGA)-tuning to use a greater variety of objective functions, improving its chances of finding better quality non-dominated solutions in a shorter time span. Bi-directional dynamic bumpless transfer was added to effect smooth transfer between the controllers.A unique way of improving the MOGA-tuning of the fuzzy logic controller was also employed by optimizing the number of input membership functions and their initial positions using fuzzy data clustering and adaptive neuro-fuzzy inference system data training techniques, and also by optimizing the number of generations required for convergence.Finally enhancements to the visualization properties of the MOGA’s graphical user interface (GUI) relating to its trade-off graph of parallel coordinates were implemented. These included percentage objective trade-off information in tabular matrix and bar chart form, and the incorporation of an evolving conflict or trade-off sensitivity mechanism to improve the visualization of the trade-off graph. These improvements were carried out to give the decision maker a better understanding of the system’s characteristics, and in doing so, to enhance the chances of a successful outcome when deciding between non-dominated solutions or potential fuzzy controller inference systems.<br/
Improved MOGA-tuning and visualization for a hybrid control system
Full text linkA hybrid controller is developed for a solar-thermal power plant using a gain-scheduled controller with feedforward to control the more linear operating regimes and a fuzzy PI incremental controller for the highly nonlinear operating region of the plant. An enhanced method of MOGA-tuning is employed by first optimizing the number of input/output membership functions using neuro-fuzzy data clustering. Enhancements to the visualization properties of the MOGA's graphical user interface are evaluated to improve the decision maker's choice when deciding between non-dominated solutions or potential fuzzy controller inference systems
Hybrid control using evolutionary tuned fuzzy controller techniques - a study
No full textMany real world systems exist that have operating regions or regimes that exhibit varying degrees of non-lineararity. An example of this are the significant variations in the dynamic characteristics of a distributed collector field within a solar power plant. Her a gain schedule controller using pole placement with feedforward was chosen to control the more linear operating regimes of the plant. Then a study was carried out to find the best suited and most efficient evolutionary-tuned fuzzy logic based controller, for rexlusive and concentrated use on the plant's more non-linear regions
Going Beyond Counting First Authors in Author Co-citation Analysis
Full text linkThe present study examines one of the fundamental aspects of author co-citation analysis (ACA) - the way co-citation
counts are defined. Co-citation counting provides the data on which all subsequent statistical analyses and mappings
are based, and we compare ACA results based on two different types of co-citation counting - the traditional type that
only counts the first one among a cited work's authors on the one hand and a non-traditional type that takes into
account the first 5 authors of a cited work on the other hand. Results indicate that the picture produced through this non-traditional author co-citation counting contains more coherent author groups and is therefore considerably clearer. However, this picture represents fewer specialties in the research field being studied than that produced through the traditional first-author co-citation counting when the same number of top-ranked authors is selected and analyzed. Reasons for these effects are discussed
Variations on the Author
Full text link“Variations on the Author” discusses two of Eduardo Coutinho’s recent films (Um Dia na Vida, from 2010, and Últimas Conversas, posthumously released in 2015) and their contribution to the general question of documentary authorship. The director’s filmography is characterized by a consistent yet self-effacing form of authorial self-inscription: Coutinho often features as an interviewer that rather than express opinions propels discourses; an interviewer that is good at listening. This mode of self-inscription characterizes him as an author who is not expressive but who is nonetheless markedly present on the screen. In Um Dia na Vida, however, Coutinho is completely absent form the image, while Últimas Conversas, on the contrary, includes a confessional prologue that moves the director from the margins to the center of his films. This article examines the ways in which these works stand out in the filmography of a director who offers new insights into the notion of cinematic authorship
Appropriate Similarity Measures for Author Cocitation Analysis
Full text linkWe provide a number of new insights into the methodological discussion about author cocitation analysis. We first argue that the use of the Pearson correlation for measuring the similarity between authors’ cocitation profiles is not very satisfactory. We then discuss what kind of similarity measures may be used as an alternative to the Pearson correlation. We consider three similarity measures in particular. One is the well-known cosine. The other two similarity measures have not been used before in the bibliometric literature. Finally, we show by means of an example that our findings have a high practical relevance.information science;Pearson correlation;cosine;similarity measure;author cocitation analysis
Gain-scheduled control of a solar power plant using a hierarchical MOGA-tuned fuzzy Pi-Controller
No full textIn order to regulate the significant variations in the dynamic characteristics of a distributed collector field in a solar power plant, various control techniques including feedforward control, gain scheduling and fuzzy control have been considered in the past. This paper develops some of these previous approaches by considering the operating conditions of the plant and the desired controlled responses. The result is a control scheme that employs a fuzzy PI controller, with feedforward, for the highly nonlinear part of the operating regime and gain scheduled control over the more linear part of the operating envelope. In order to satisfy performance characteristics for the plant at different points in the operating regime, a multiobjective genetic algorithm is used to design the parameters of the fuzzy controller. To reduce the size of the search space and the resulting fuzzy controller, a hierarchical encoding is employed with the multiobjective genetic algorithm. The resulting controller is shown to both satisfy the desired performance criteria and have a reduced number of terms compared with a conventional design approac
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