Robust Adaptive Cooperative Control for Formation-Tracking Problem in a Network of Non-Affine Nonlinear Agents

In this chapter, a decentralized cooperative control protocol is proposed with application to any network of agents with non-affine nonlinear multi-input-multi-output (MIMO) dynamics. Here, the main purpose of cooperative control protocol is to track a time-variant reference trajectory while maintaining a desired formation. The reference trajectory is defined to a leader, which has at least one information connection with one of the agents in the network. The design procedure includes a robust adaptive law for estimating the unknown nonlinear terms of each agent’s dynamics in a model-free format, that is, without the use of any regressors. Moreover, an observer is designed to have an approximation on the values of control parameters for the leader at the agents without connection to the leader. The entire design procedure is analysed successfully for the stability using Lyapunov stability theorem. Finally, the simulation results for the application of the proposed method on a network of nonholonomic wheeled mobile robots (WMR) are presented. Desirable leader-following tracking and geometric formation control performance have been successfully demonstrated through simulated group of wheeled mobile robots

Adaptive Model-Free Control And Localization For Single-Agent And Multi-Agent Nonlinear Dynamic Systems

In this thesis, a unified solution comprising model-free control and localization algorithms is presented to address the tracking problem in single-agent completely unknown nonlinear dynamic systems, the formation-tracking problem in multi-agent completely unknown nonlinear dynamic system, and the cooperative localization problem for a team of mobile agents. The formulated model-free control algorithms, neither rely on the universal approximation characteristic of the artificial neural networks nor regressor-based approximation

Methodology of Acquiring Valid Data by Combining Oil Tankers’ Noon Report and Automatic Identification System Satellite Data

Fuel consumption of marine vessels plays an important role in both generating air pollution and ship operational expenses where the global environmental concerns toward air pollution and economics of shipping operation are being increased. In order to optimize ship fuel consumption, the fuel consumption prediction for her envisaged voyage is to be known. To predict fuel consumption of a ship, noon report (NR) data are available source to be analysed by different techniques. Because of the possible human error attributed to the method of NR data collection, it involves risk of possible inaccuracy. Therefore, in this study, to acquire pure valid data, the NR raw data of two very large crude carriers (VLCCs) composed with their respective Automatic Identification System (AIS) satellite data. Then, well-known models i.e. K-Mean, Self-Organizing Map (SOM), Outlier Score Base (OSB) and Histogram of Outlier Score Base (HSOB) methods are applied to the collected tankers NR during a year. The new enriched data derived are compared to the raw NR to distinguish the most fitted methodology of accruing pure valid data. Expected value and root mean square methods are applied to evaluate the accuracy of the methodologies. It is concluded that measured expected value and root mean square for HOSB are indicating high coherence with the harmony of the primary NR data.</p

Crowdfunding Project Success for Game Developers: Evidence from Kickstarter and Steam

Crowdfunding has revolutionized business investor connection in many industries, one of which is game development. Traditionally, triple-A game developers and publishers were able to monopolize the industry, but with the emergence of crowdfunding platforms, smaller game development teams and companies have a way of competing with large corporations by attracting funds. However, Kickstarter reports show that two-third of game funding projects fail to meet their goals. This study develops and empirically examines a theoretical model to predict video game’s crowdfunding success to address this gap. We collect data on video game projects that were initiated on Kickstarter and were later released on the Steam platform. Our analysis of more than 7000 reward tiers for 1967 projects reveals that reward type (free game copy, in-game perks, accessories, artworks, and involvement), and reward description length positively influence funding success, while the number of reward tiers and funding period negatively impact funding success

Wearable smart blanket system model for monitoring the vital signs of patients in ambulance

Introduction: The timely and managed intervention reduces the consequences of disease and sudden death among the patients in emergency conditions. Monitoring the patients in emergency conditions requires rapid and appropriate decisions to save their lives. The present study aimed at modeling the wearable smart blanket system for monitoring the patients in the emergency conditions of ambulance. Materials and Methods: The present study was based on an applied and descriptive-developmental design. Firstly, the requirements and features of wearable smart blanket system were elicited and secondly a smart blanket system was modeled by using the UML charts and elicited requirements. Finally, the designed architecture was evaluated using ARID scenario-based method. Results: The functional requirements of wearable smart blanket system with its data elements and physical-structural features of this system as well as non-functional requirements were elicited. Based on the requirements and data elements elicited from the questionnaire, class diagram, activity, use-case diagram, sequence, deployment, and component were drawn. Then, using the UML and the relationships between components, systems, and users from the structural and behavioral perspectives used the ARID scenario-based evaluation method to indicate that the designed architecture could provide the expected scenarios from the proposed system. Conclusion: Wearable smart blanket system collects the data related to medical signals by the sensors installed on the blanket and such data are processed by the smart system. Therefore, it can be concluded that the design of this system makes it possible to monitor and control patients in risky conditions with better quality and to integrate vital signs. The analyzing biological data makes it easy for doctors to take early diagnosis and intervention

Association of Family History of Epilepsy with Earlier Age Onset of Juvenile Myoclonic Epilepsy

How to Cite This Article: Najafi MR, Najafi MA, Safaei A. Association of Family History of Epilepsy with Earlier Age Onset of Juvenile Myoclonic Epilepsy. Iran J Child Neurol. Spring 2016; 10(2):10-15.AbstractObjectiveJuvenile myoclonic epilepsy (JME) is supposedly the most frequent subtype of idiopathic generalized epilepsies (IGE). The aim of this study was to determine the prevalence of JME and comparison of patients’ demographics as well as timeline of the disease between positive family history epileptic patients (PFHE) and negative family history epileptic patients (NFHE) among sample of Iranian epileptic patients.Materials &amp; MethodsFrom Feb. 2006 to Oct. 2009, 1915 definite epileptic patients (873 females) referred to epilepsy clinics in Isfahan, central Iran, were surveyed and among them, 194 JME patients were diagnosed. JME was diagnosed by its specific clinical and EEG criteria. Patients were divided into two groups as PFHE and NFHE and data were compared between them.ResultsJME was responsible for 10% (194 patients) of all types of epilepsies. Of JME patients, 53% were female. In terms of family history of epilepsy, 40% were positive. No significant differences was found between PFHE and NFHE groups as for gender (P&gt;0.05). Age of epilepsy onset was significantly earlier in PFHE patients (15 vs. 22 yr, P&lt;0.001). Occurrence of JME before 18 yr old among PFHE patients was significantly higher (OR=2.356, P=0.007).ConclusionA family history of epilepsy might be associated with an earlier age of onset in patients with JME. References1. Banerjee PN, Filippi D, Allen Hauser W. The descriptive epidemiology of epilepsy—a review. Epilepsy Res 2009;85(1):31-45.2. Khedr EM, Shawky OA, Ahmed MA, Elfetoh NA, Al Attar G, Ali AM, et al. A community based epidemiological study of epilepsy in Assiut Governorate/Egypt. Epilepsy Res 2013;103(2):294-302.3. 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