Sharif Digital Repository

In this paper a new control strategy for adaptive attitude control of multivariable satellite system has been presented. The approach is based on radial basis function neural network (RBFNN). By using four reaction wheels and Modified Rodrigues Parameters (MRPs) for attitude representation, the attitude dynamic of satellite has been considered. The Lyapunov stability theory has been used to achieve a stable closed loop system. Also to enhance the robustness of the controller, the RBF neural network has been employed to estimate the model base terms in control law. The control objective is the plant to track a reference model. Simulation results illustrate the performance of the on-line... 

In this paper an off-line ArabiclFarsi handwritten recognition Algorithm on a subset of Farsi name is proposed. In this system, There is no sub-word segmentation phase. Script database includes 3300 images of 30 Farsi common names. The features are wavelet coefficients extracted from smoothed word image profiles in four standard directions. The Centers of competitive layer of RBF neural network have been determined by combining GA and K-Means clustering algorithm. Weights of supervised layer has been trained by using LMS rule and the distances of feature vector of each sample to the centre of RBF network have been computed based on warping function. Experimental results show advantages of... 

This work presents a method to increase the face recognition accuracy using a combination of Wavelet, PCA, KPCA, and RBF Neural Networks. Preprocessing, feature extraction and classification rules are three crucial issues for face recognition. This paper presents a hybrid approach to employ these issues. For preprocessing and feature extraction steps, we apply a combination of wavelet transform, PCA and KPCA. During the classification stage, the Neural Network (RBF) is explored to achieve a robust decision in presence of wide facial variations. At first derives a feature vector from a set of downsampled wavelet representation of face images, then the resulting PCA-based linear features and... 

Proposing an efficient algorithm with an appropriate hardware implementation has always been an interesting and a rather challenging field of research in Artificial Intelligence (AI). Fuzzy logic is one of the techniques that can be used for accurate and high-speed modeling as well as controlling complex and nonlinear systems. The “defuzzification” process during the test phase as well as the repetitive processes in order to find the optimal parameters during the training phase, lead to some serious limitations in real-time applications and hardware implementation of these algorithms. The proposed algorithm employs Ink Drop Spread (IDS) concept to mimic the functionality of human brain. In... 

The assessment of the hypnotic state of the brain is crucial to the process of an operation under general anaesthesia. A noninvasive method of quantifying depth of anaesthesia is through analysis of electroencephalogram (EEG). Among number of works done in the field, no single algorithm has been found exhibiting a precise measure in all of the hypnotic states. One can categorise algorithms as either a state-quantifier or a trend measure. State-quantifier algorithms can discriminate between different hypnotic states such as awake, light sedation, deep anaesthesia, etc. On the other hand, trend measure algorithms are employed to specify the short-term changes in hypnotic brain conditions,... 

In this study, the fatigue performance of AISI 304 subjected to shot peening (SP), ultrasonic nanocrystal surface modification (UNSM) and the combination of SP + UNSM processes was systematically assessed by rotary bending fatigue (RBF) tester at different stress levels. The purpose of combining SP and UNSM processes is to find out whether SP following UNSM process can further improve the fatigue life of AISI 304 in comparison with the SP and UNSM processes alone. Interestingly, the fatigue strength of AISI 304 was deteriorated by the combination of SP + UNSM processes in comparison with the UNSM process alone, but the combination of SP + UNSM processes demonstrated a higher fatigue strength... 

This paper deals with the solution of two-dimensional fluid flow problems using the truly meshless Local Petrov-Galerkin (MLPG) method. The present method is a truly meshless method based only on a number of randomly located nodes. Radial basis functions (RBF) are employed for constructing trial functions in the local weighted meshless local Petrov-Galerkin method for two-dimensional transient viscous fluid flow problems. No boundary integration is needed, no element matrix assembly is required and no special treatment is needed to impose the essential boundary conditions due to satisfaction of kronecker delta property in RBFs. Three different radial basis functions (RBFs), i.e.... 

This paper presents a comparative study of various soft computing algorithms for reconstruction of neutron noise sources in the nuclear reactor cores. To this end, the computational code for reconstruction of neutron noise source is developed based on the Adaptive Neuro-Fuzzy Inference System (ANFIS), Decision Tree (DT), Radial Basis Function (RBF) and Support Vector Machine (SVM) algorithms. Neutron noise source reconstruction process using the developed computational code consists of three stages of training, testing and validation. The information of neutron noise sources and induced neutron noise distributions are used as output and input data of training stage, respectively. As input... 

A control strategy on a hybrid vehicle can be implemented through different methods. In this paper, the Cerebellar Model Articulation Controller (CMAC) and Radial Basis Function (RBF) neural networks were applied to develop an optimal control strategy for a split parallel hydraulic hybrid vehicle. These networks contain a nonlinear mapping, and, also, the fast learning procedure has made them desirable for online control. The RBF network was constructed with the use of the K-mean clustering method, and the CMAC network was investigated for different association factors. Results show that the binary CMAC has better performance over the RBF network. Also, the hybridization of the vehicle... 

In the recent years due to increasing demand for energy and declination of reservoir production, an impressive notice on enhancement of oil recovery has been found. The gas injection especially carbon dioxide injection due to low cost and friendly environmentally of this approach the special attention to CO2 injection increased. The miscibility is known as key factor which effects on enhancement of recovery. The miscibility is controlled by interfacial tension of hydrocarbons and carbon dioxide so the importance of investigation of the interfacial tension becomes highlighted.in this investigation by using radial basis function (RBF) artificial neural network (ANN) as a novel approach the... 

Individual and synergy effects of shot peening (SP) and ultrasonic nanocrystal surface modification (UNSM) on rotary bending fatigue (RBF) behavior of AISI 4340 steel were systematically investigated at various bending stress levels in the range of 275–600 MPa. The results revealed that the fatigue behavior of the as-received sample was enhanced by SP and it was further enhanced by SP and UNSM combination, while the UNSM-treated one exhibited the highest enhancement in fatigue behavior. The fatigue behavior of the SP + UNSM sample was enhanced after SP, but it was found to be detrimental after UNSM. Apart from RBF experiments, individual and synergy effects of SP and UNSM on surface... 

In this paper, an adaptive multi-model sliding mode controller for robotic manipulators is presented. By using the multiple models technique, the nominal part of the control signal is constructed according to the most appropriate model at different environments. Adaptive single-input-single-output (SISO) fuzzy systems or radial basis function (RBF) neural networks, regarding their functional equivalence property, are used to approximate the discontinuous part of control signal; control gain, in a classical sliding mode controller. The key feature of this scheme is that prior knowledge of the system uncertainties is not required to guarantee the stability. Also the chattering phenomenon in... 

The process of local scour around bridge piers is fundamentally complex due to the three-dimensional flow patterns interacting with bed materials. For geotechnical and economical reasons, multiple pile bridge piers have become more and more popular in bridge design. Although many studies have been carried out to develop relationships for the maximum scour depth at pile groups under clear-water scour condition, existing methods do not always produce reasonable results for scour predictions. It is partly due to the complexity of the phenomenon involved and partly because of limitations of the traditional analytical tool of statistical regression. This paper addresses the latter part and... 

Numerous methods have been proposed previously to describe the characterization of porous materials; however, no well-developed theory is still available. Three different modeling methods were employed in this study to explore the relationship between the characterization parameters of activated carbon (AC) and its methane uptake. The first and the second methods were based on the Radial Basis Function (R.B.F) neural networks. At the first R.B.F. modeling, the neural networks algorithm was designed using the Gaussian function. The collected data for modeling were divided into two parts; (i) the data used for training the network and (ii) the data used for testing the predicted network. At...