The paper present design of a control structure that enables integration of a Kinematic neural controller for trajectory tracking of a nonholonomic differential two wheeled mobile robot, then proposes a Kinematic neural controller to direct a National Instrument mobile robot (NI Mobile Robot). The controller is to make the actual velocity of the wheeled mobile robot close the required velocity by guarantees that the trajectory tracking mean squire error converges at minimum tracking error. The proposed tracking control system consists of two layers; The first layer is a multi-layer perceptron neural network system that controls the mobile robot to track the required path , The second layer is an optimization layer ,which is implemented based on hybrid Crossoved Firefly Algorithm with Artificial Bee Colony (CFA-ABC) to tune the controller's parameters to achieve the optimal path. The performance of the hybrid optimization algorithm is verified by various benchmark functions. The simulation results show that the utilizing of CFA and (CFA-ABC ) are better than the original Firefly Algorithm. A simulation example is given to indicate the effectiveness of the proposed algorithm, the results have been done using MATLAB (R2013b), and all trajectory tracking results with two reference trajectories (circular and lemniscates ) are presented.
Abstract
This study aims to identify the extent to which the criteria of the American Council for Teaching Foreign Languages (ACTFL) are included in the English language books for the fifth and sixth graders. To achieve the objective of the study, a content analysis card was prepared, where the classification of language proficiencies was divided into five main levels (beginner, intermediate, advanced, superior, and distinguished) of the four language skills (listening, speaking, reading, and writing), The content analysis card consisted of (89) indicators distributed at the four levels of language skills as follows: Listening (17), speaking (33), reading (15), and writing (26). The study sample consisted of Engl
... Show MoreIn this study, an analysis of re-using the JPEG lossy algorithm on the quality of satellite imagery is presented. The standard JPEG compression algorithm is adopted and applied using Irfan view program, the rang of JPEG quality that used is 50-100.Depending on the calculated satellite image quality variation, the maximum number of the re-use of the JPEG lossy algorithm adopted in this study is 50 times. The image quality degradation to the JPEG quality factor and the number of re-use of the JPEG algorithm to store the satellite image is analyzed.
In this paper we proposes the philosophy of the Darwinian selection as synthesis method called Genetic algorithm ( GA ), and include new merit function with simple form then its uses in other works for designing one of the kinds of multilayer optical filters called high reflection mirror. Here we intend to investigate solutions for many practical problems. This work appears designed high reflection mirror that have good performance with reduction the number of layers, which can enable one to controlling the errors effect of the thickness layers on the final product, where in this work we can yield such a solution in a very shorter time by controlling the length of the chromosome and optimal genetic operators . Res
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In the present study, composites were prepared by Hand lay-up molding. The composites constituents were epoxy resin as a matrix, 6% volume fractions of glass fibers (G.F) as reinforcement and 3%, 6% volume fractions of preparation natural material (Rice Husk Ash, Carrot Powder, and Sawdust) as filler. Studied the erosion wear behavior and coating by natural wastes (Rice Husk Ash) with epoxy resin after erosion. The results showed the non – reinforced epoxy have lower resistance erosion than natural based material composites and the specimen (Epoxy+6%glass fiber+6%RHA) has higher resistance erosion than composites reinforced with carrot powder and sawdust at 30cm , angle 60
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In this work, diabetic glucose concentration level control under disturbing meal has been controlled using two set of advanced controllers. The first set is sliding mode controllers (classical and integral) and the second set is represented by optimal LQR controllers (classical and Min-, ax). Due to their characteristic features of disturbance rejection, both integral sliding mode controller and LQR Minmax controller are dedicated here for comparison. The Bergman minimal mathematical model was used to represent the dynamic behavior of a diabetic patient’s blood glucose concentration to the insulin injection. Simulations based on Matlab/Simulink, were performed to verify the performance of each controll
... Show MoreSeveral stress-strain models were used to predict the strengths of steel fiber reinforced concrete, which are distinctive of the material. However, insufficient research has been done on the influence of hybrid fiber combinations (comprising two or more distinct fibers) on the characteristics of concrete. For this reason, the researchers conducted an experimental program to determine the stress-strain relationship of 30 concrete samples reinforced with two distinct fibers (a hybrid of polyvinyl alcohol and steel fibers), with compressive strengths ranging from 40 to 120 MPa. A total of 80% of the experimental results were used to develop a new empirical stress-strain model, which was accomplished through the application of the parti
... Show MoreA Wearable Robotic Knee (WRK) is a mobile device designed to assist disabled individuals in moving freely in undefined environments without external support. An advanced controller is required to track the output trajectory of a WRK device in order to resolve uncertainties that are caused by modeling errors and external disturbances. During the performance of a task, disturbances are caused by changes in the external load and dynamic work conditions, such as by holding weights while performing the task. The aim of this study is to address these issues and enhance the performance of the output trajectory tracking goal using an adaptive robust controller based on the Radial Basis Function (RBF) Neural Network (NN) system and Hamilton
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