Browsing by Subject "Intelligent systems"
Now showing 1 - 10 of 10
Results Per Page
Sort Options
Item Open Access A 3D dynamic model of a spherical wheeled self-balancing robot(2012) İnal, Ali Nail; Morgül, Ömer; Saranlı, UluçMobility through balancing on spherical wheels has recently received some attention in the robotics literature. Unlike traditional wheeled platforms, the operation of such platforms depends heavily on understanding and working with system dynamics, which have so far been approximated with simple planar models and their decoupled extension to three dimensions. Unfortunately, such models cannot capture inherently spatial aspects of motion such as yaw motion arising from the wheel rolling motion or coupled inertial effects for fast maneuvers. In this paper, we describe a novel, fully-coupled 3D model for such spherical wheeled platforms and show that it not only captures relevant spatial aspects of motion, but also provides a basis for controllers better informed by system dynamics. We focus our evaluations to simulations with this model and use circular paths to reveal advantages of this model in dynamically rich situations. © 2012 IEEE.Item Open Access Adaptive control design for nonlinear systems via successive approximations(ASME, 2017) Babaei, N.; Salamcı, M. U.; Karakurt, Ahmet HakanThe paper presents an approach to the Model Reference Adaptive Control (MRAC) design for nonlinear dynamical systems. A nonlinear reference system is considered such that its response is designed to be stable via Successive Approximation Approach (SAA). Having designed the stable reference model through the SAA, MRAC is then formulated for nonlinear plant dynamics with a new adaptation rule to guarantee the convergence of the nonlinear plant response to that of the response of the nonlinear reference model. The proposed design methodology is illustrated with examples for different case studies.Item Open Access Benefits of forecasting and energy storage in isolated grids with large wind penetration – The case of Sao Vicente(Elsevier, 2017) Yuan, S.; Kocaman, A.S.; Modi, V.For electric grids that rely primarily on liquid fuel based power generation for energy provision, e.g. one or more diesel gensets, measures to allow a larger fraction of intermittent sources can pay-off since the displaced is high cost diesel powered generation. This paper presents a case study of Sao Vicente, located in Cape Verde where a particularly high fraction of wind capacity of 5.950�MW (75% of the average demand) is installed, with diesel gensets forming the dispatchable source of power. This high penetration of intermittent power is managed through conservative forecasting and curtailments. Two potential approaches to reduce curtailments are examined in this paper: 1) an improved wind speed forecasting using a rolling horizon ARIMA model; and 2) energy storage. This case study shows that combining renewable energy forecasting and energy storage is a promising solution which enhances diesel fuel savings as well as enables the isolated grid to further increase the annual renewable energy penetration from the current 30.4% up to 38% while reducing grid unreliability. In general, since renewable energy forecasting ensures more accurate scheduling and energy storage absorbs scheduling error, this solution is applicable to any small size isolated power grid with large renewable energy penetration.Item Open Access Comparative analysis of different approaches to target classification and localization with sonar(IEEE, 2001-08) Ayrulu, Birsel; Barshan, BillurThe comparison of different classification and fusion techniques was done for target classification and localization with sonar. Target localization performance of artificial neural networks (ANN) was found to be better than the target differentiation algorithm (TDA) and fusion techniques. The target classification performance of non-parametric approaches was better than that of parameterized density estimator (PDE) using homoscedastic and heteroscedastic NM for statistical pattern recognition techniques.Item Open Access Developing a text categorization template for Turkish news portals(IEEE, 2011) Toraman, Çağrı; Can, Fazlı; Koçberber, SeyitIn news portals, text category information is needed for news presentation. However, for many news stories the category information is unavailable, incorrectly assigned or too generic. This makes the text categorization a necessary tool for news portals. Automated text categorization (ATC) is a multifaceted difficult process that involves decisions regarding tuning of several parameters, term weighting, word stemming, word stopping, and feature selection. In this study we aim to find a categorization setup that will provide highly accurate results in ATC for Turkish news portals. We also examine some other aspects such as the effects of training dataset set size and robustness issues. Two Turkish test collections with different characteristics are created using Bilkent News Portal. Experiments are conducted with four classification methods: C4.5, KNN, Naive Bayes, and SVM (using polynomial and rbf kernels). Our results recommends a text categorization template for Turkish news portals and provides some future research pointers. © 2011 IEEE.Item Open Access Effects of linear filter on stability and performance of human-in-the-loop model reference adaptive control architectures(ASME, 2017) Yousefi, Ehsan; Demir, Didem Fatma; Sipahi, R.; Yücelen, T.; Yıldız, YıldırayModel reference adaptive control (MRAC) can effectively handle various challenges of the real world control problems including exogenous disturbances, system uncertainties, and degraded modes of operations. In human-in-the-loop settings, MRAC may cause unstable system trajectories. Basing on our recent work on the stability of MRAC-human dynamics, here we follow an optimization based computations to design a linear filter and study whether or not this filter inserted between the human model and MRAC could help remove such instabilities, and potentially improve performance. To this end, we present a mathematical approach to study how the error dynamics of MRAC could favorably or detrimentally influence human operator's error dynamics in performing a certain task. An illustrative numerical example concludes the study.Item Open Access Kinect based intelligent wheelchair navigation with potential fields(IEEE, 2014) Özçelikörs, M.; Çoşkun, A.; Say, M. Girayhan; Yazici, A.; Yayan, U.; Akçakoca, M.Increasing elderly people population and people with disabilities constitute a huge demand for wheelchairs. Wheelchairs have an important role on improving the lives and mobilization of people with disabilities. Moreover, autonomous wheelchairs constitute a suitable research platform for academic and industrial researchers. In this study, Finite state machine (FSM) based high-level controller and Kinect based navigation algorithm have been developed for ATEKS (Intelligent Wheelchair) which has high-tech control mechanisms, low-cost sensors and open source software (ROS, GAZEBO, ANDROID). © 2014 IEEE.Item Open Access Reward-rate maximization in sequential identification under a stochastic deadline(2013) Dayanık, S.; Yu, A. J.Any intelligent system performing evidence-based decision making under time pressure must negotiate a speed-accuracy trade-off. In computer science and engineering, this is typically modeled as minimizing a Bayes-risk functional that is a linear combination of expected decision delay and expected terminal decision loss. In neuroscience and psychology, however, it is often modeled as maximizing the long-term reward rate, or the ratio of expected terminal reward and expected decision delay. The two approaches have opposing advantages and disadvantages. While Bayes-risk minimization can be solved with powerful dynamic programming techniques unlike reward-rate maximization, it also requires the explicit specification of the relative costs of decision delay and error, which is obviated by reward-rate maximization. Here, we demonstrate that, for a large class of sequential multihypothesis identification problems under a stochastic deadline, the reward-rate maximization is equivalent to a special case of Bayes-risk minimization, in which the optimal policy that attains the minimal risk when the unit sampling cost is exactly the maximal reward rate is also the policy that attains maximal reward rate. We show that the maximum reward rate is the unique unit sampling cost for which the expected total observation cost and expected terminal reward break even under every Bayes-risk optimal decision rule. This interplay between reward-rate maximization and Bayesrisk minimization formulations allows us to show that maximum reward rate is always attained. We can compute the policy that maximizes reward rate by solving an inverse Bayes-risk minimization problem, whereby we know the Bayes risk of the optimal policy and need to find the associated unit sampling cost parameter. Leveraging this equivalence, we derive an iterative dynamic programming procedure for solving the reward-rate maximization problem exponentially fast, thus incorporating the advantages of both the reward-rate maximization and Bayes-risk minimization formulations. As an illustration, we will apply the procedure to a two-hypothesis identification example.Item Open Access Self-assembled peptide nanostructures for functional materials(Institute of Physics Publishing, 2016) Ekiz, M. S.; Cinar, G.; Khalily, M. A.; Güler, Mustafa O.Nature is an important inspirational source for scientists, and presents complex and elegant examples of adaptive and intelligent systems created by self-assembly. Significant effort has been devoted to understanding these sophisticated systems. The self-assembly process enables us to create supramolecular nanostructures with high order and complexity, and peptide-based self-assembling building blocks can serve as suitable platforms to construct nanostructures showing diverse features and applications. In this review, peptide-based supramolecular assemblies will be discussed in terms of their synthesis, design, characterization and application. Peptide nanostructures are categorized based on their chemical and physical properties and will be examined by rationalizing the influence of peptide design on the resulting morphology and the methods employed to characterize these high order complex systems. Moreover, the application of self-assembled peptide nanomaterials as functional materials in information technologies and environmental sciences will be reviewed by providing examples from recently published high-impact studies.Item Open Access Towards a quality service layer for Web 2.0(Springer, 2011-12) Schaal, M.; Davenport, David; Çevik, Ali HamdiDespite the help of search engines and Web directories, identifying high quality content becomes increasingly difficult as the Internet gets ever more crowded with information. Prior approaches for filtering and searching content with respect to user-specific preferences do exist: Recommendation engines employ collaborative filtering to support subjective selection, (semi-)automatic page ranking algorithms utilize the hypertext link structure of the World Wide Web to assess page importance, and trust-based systems employ social network analysis to determine the most suitable Web pages. The use of implicit and explicit user feedback, however, is often either ignored or its exploitation is limited to isolated Web sites. We thus propose a quality overlay framework that enables the collection and processing of user-feedback, and the subsequent presentation of quality-enabled content for any Web-site. We present the quality overlay framework, propose an architecture for its realization, and validate our approach by scenarios and a detailed design with sample implementation. © 2011 Springer-Verlag.