Sharif Digital Repository

In this study, for the first time, a comprehensive and online framework for active control of beams subjected to the moving mass is presented. In active control problems, comprehensive knowledge of system states is required to determine the control force, but it is not possible to measure all system states in practice with a limited number of sensors. In this regard, Kalman filters are introduced to control systems to help improve the performance of control systems as observers of system states. However, in the case of beams subjected to the moving mass, due to the moving nature of the passing mass, in addition to system states, it is also important to identify the input load. In previous... 

Today, considering the global demand for reducing greenhouse gas emissions, rechargeable batteries are considered as a source of energy in electric vehicles, hybrid electric vehicles and smart grids. In all these applications for secondary batteries, the battery management system requires an accurate estimate state of charge of each cell. However, this estimate is difficult particularly for battery aging. In this study, a lithium-ion battery is modeled by using multidimensional multiphysics modeling and simulated in a comsol. In this simulation, the effect of the thermal conductivity coefficient on the battery temperature, initial salt concentration in electrolyte and the rate of discharge... 

Epilepsy is a neurological disorder whose prevalence is estimated to be 1% of the world population. Electroencephalogram (EEG) is one of the best and convenient non-invasive tools used in diagnosis and analysis of this disease. Epileptic components extracted from EEG recordings are widely used in neuroscience in the diagnosis analysis like epilepsy source localization. However, epileptic components are often contaminated and covered with artifacts of physiological origin (baseline, EMG, ECG, EOG, etc.) or instrument noises (power supply, electrode, etc.). So, preprocessing and denoising is necessary for precise analysis of epilepsy EEG recording. Heretofore, several methods have been... 

In this study pain level estimation using facial expression is investigated. To do this, there are two approaches, one approach is sequence level pain estimation and the other one is frame level pain estimation. In sequence level, after feature extraction from all frames of sequence, each sequence is represented by a fixed length feature vector, this feature vector is constructed by concatenating min, max and mean of frame features of that specific sequence, then KLPP is applied in order to reduce feature vector dimension and in the end a linear regression is implemented to predict the pain labels of the sequence. In the frame level, two approaches are introduced, the first one is based on... 

Gene regulatory modeling in different species is one of the main aims of Bioinformatics. Regarding the limitations of the data available and the perspectives which should be taken into account for modeling such networks, proposed methods up to now have not yet been successful in yielding a comprehensive model. In one of the recent researches, the Gene regulation process is considered as a nonlinear dynamic stochastic process and described by state space equations. Afterwards, in order for the unknown parameters to be estimated, Extended Kalman Filtering is used. In this thesis, first of all, Gene complexes are taken into consideration instead of genes and afterwards, Extended Kalman... 

Recently, parametric excitation has been proposed and experimentally proven to provide micro gyroscopes with robustness to parameter variations and enhancement of sensitivity [L.A. Oropeza-Ramos, C.B. Burgner, K.L. Turner, Robust micro-rate sensor actuated by parametric resonance, Sensors and Actuators A: Physical, 152 (2009) 80-87].The first part of this thesis aims at investigating the nonlinear dynamics of MEMS vibratory gyroscopes with parametric excitation which can be represented by a minor variation of nonlinear Mathieu equation coupled to a Duffing oscillator. Our approach is based on analytical frequency response derivation via method of multiple time scales. Stability of responses,... 

In this thesis, the orbit determination of Low Earth Orbits (LEO) using the integrated magnetometer and horizon sensor data has been investigated. Orbit determination is an essential part of a space mission. Not only the modeling, guidance, navigation and control errors may results in error in injecting the satellite into its nominal orbit, the environmental disturbances deviate the satellite from its predicted orbit and from an operational perspective most satellites need continuous orbit determination. Traditionally, ground based orbit determination is used which are non-autonomous and expensive and just can be used for specific times which the satellite can be observed from the ground... 

Nowadays, application of AUVs in marine missions is a crucial research field. To reach a fully automated underwater vehicle, it should suitably be designed, controlled, navigated and its fault is detected immediately. An Identified model of AUV is usable for all of these goals. Thus, in this project, parameters of an appropriate dynamic model of AUV is estimated using augmented state space method and TUKF.By investigating possibility of parameter estimation of 6-DOF model and sub models in different cases, a scenario for estimation of cruise, steering and diving sub model parameters of AUV, using output of DVL and Gyroscope is proposed. Furthermore, planar misalignment between DVL and IMU,... 

The estimation of attitude and deformation of a flexible satellite using magnetometer and sun sensor data are studied in this thesis. To this end, the dynamical differential equations of the flexible satellite have been derived using Lagrange’s equation. These equations of motion are then utilized for the purpose of simulation and verification. After introducing the measurements equations, the observability of the satellite with flexible panels has been evaluated. Afterward, the attitude of the satellite body and deformation of the flexible panels have been estimated by EKF (Extended Kalman Filter) as well as UKF (Unscented Kalman Filter). The results show that the estimations using UKF are... 

The aim of tracking is localization and positioning of position-variant object through consecutive times. The essence of this object determines the application of tracking. For example this object can be the satellite, mobile, certain object in sequential movie or etc. The particle filter as an estimation filter is a method that provides us the solution of tracking Problem. Therefore this thesis is devoted to particle filter and its application in tracking. But tracking problem needs some prior information; one of them is access to measurements relating to object position. In situations that the measurement equation which is related to object position has ambiguity we need another mechanism... 

Due to various applications of human motion capture techniques, developing low-cost methods that would be applicable in non-laboratory environments is under consideration. MEMS inertial sensors and Kinect are two low-cost devices that can be utilized in home-based motion capture systems, e.g. home-based rehabilitation. In this work, an unscented Kalman filter approach was developed based on the complementary properties of Kinect and the inertial sensors to fuse the orientation data of these two devices for human arm motion tracking during both stationary shoulder joint position and human body movement. A new measurement model of the fusion algorithm was obtained that can compensate for the... 

Robot navigation and guidance is an important issue in robotic. Navigation by itself includes localization, path planning and guidance. For having a successful navigation it is necessary to succeed in all of those parts. The localization precision as basic part of localization is important and having more accurate information of robot position is important. Recently, sensors which use optical flow technic and are widely used in optical mouses are so common and they are able to measure displacement with resolution of 3 to 63 micron. In this research, a localization method for micro robot localization based on optical flow and INS sensor data fusion is presented.
Two data fusion method... 

This research proposes a Bayesian model selection framework using the stochastic filtering for rapid Bayesian identification of structures under seismic excitations. Structural identification after an earthquake at a regional scale entails a high computational effort. For rapid damage detection on a regional scale, using simplified and low-cost structural models is preferred over complex finite element models, due to the large amount of information needed for finite element modeling of numerous structures within a region as well as the high computational cost of such models. Timoshenko beams, shear beams, and shear buildings are examples of simplified structural models used in this study to... 

Human motion capture is frequently used to study rehabilitation and clinical problems, as well as to provide realistic animation for the entertainment industry. IMU based systems as well as Marker based motion tracking systems are of most popular methods to track movement due to their low cost of implementation and lightweight. Results of IMU leads to unacceptable drift errors while marker based systems are Drift-free. Also, unlike cameras, IMUs are suitable for long-distance motion capturing. Based on the complementary properties of marker based systems and the inertial sensors, in this work, an Extended Kalman Filter approach was developed to fuse the data of two IMUs and a single camera... 

Real-time asynchronous data fusion for high-speed phenomena is an important and challenging task in the sensor networks. Examples of data fusion applications in sensor networks are: managing the traffic of maneuvering airplanes and ground vehicles in airside areas of an airport, traffic management in streets and roads, Driver Assistance Systems, guidance of antiaircraft and antimissile missiles. In all the data fusion applications the estimation of the required variables is necessary.
In this research two methods are introduced for real-time asynchronous data fusion, especially for track-to-track fusion of high-speed phenomena in sensor networks. The effectiveness and usability of these... 

Nowadays, the atomic force microscopy (AFM) has become a useful laboratory tool with variety of applications. In the traditional imaging technique, usually the amplitude or frequency of AFM tip oscillations is set at a desired value using a feedback control system which is a relatively slow process. In the current research, we propose an estimation approach which uses an adaptive fading extended Kalman filter (augmented with forgetting factor) as a system observer and couples with the system dynamics to determine the sample topography. As a result, in addition to state variables of system dynamic, the sample height as an unknown parameter is estimated with high accuracy in a relatively short... 

One of the steps toward applying artificial intelligence in the field of unmanned aerial vehicles, as they are extending is the development of the controller unit and expansion of the basis of its implementation. In the beginning, one of the targets of this research is to offer an intelligent controller that utilizes an RBF neural network. Second, in order to physical parameters estimation in case of real-time system identification, an Augmented Extended Kalman Filter (AEKF) has been purposed which is capable of filtering the noise of sensors in addition to estimate some of the physical parameters. Furthermore, to check the generalization ability of the structure, three different cases of... 

This thesis aims to develop speech enhancement methods in the presence of additive noise, packet loss and band-limitation of speech signal. Noise reduction of speech improves the perceived quality and intelligibility. High performance noise reduction methods are based on Bayesian methods requiring estimates of the parameters of the functions that describe the likelihood and the prior distributions of the signal and noise processes. The Bayesian noise reduction method which is used in this thesis is Kalman filter.In packet-based speech processing applications such as Internet and Voice over Internet Protocol (VoIP), it is possibly expected that some packets during signal transmission are... 

Once the satellite is in space, it is very important to make sure that it is in its correct and prescribe orbit, along with the appropriate attitude, at any given point of time. Orbit determination and finding the exact position and velocity of a satellite is one of the most important factors in space missions. The purpose of this work is improvement in orbit determination of LEO satellites. In order to achieve this goal, combination of SGP4 and HPOP algorithms with Kalman filter is used. The HPOP algorithm uses from integration of equations of motion for finding the position and velocity of a satellite. So this algorithm is very accurate for the short time propagation, but since it is... 

Capsule endoscopy is a minimally invasive diagnostic technology for gastrointestinal diseases providing images from the human’s digestion system. Developing a robust and real-time localization algorithm to determine the orientation and position of the endoscopic capsule is a crucial step toward medical diagnostics. In this thesis, we propose a novel model-aided real-time localization approach to estimate the position and orientation of a magnetic endoscopic capsule swimming inside the stomach. In the proposed method, the governing equations of the motion of an ellipsoidal capsule inside the fluid, considering different hydrodynamics interactions, are derived. Then, based on the dynamic...