Sharif Digital Repository

Over the past years, several approaches have been used for navigation. Along with the advancement of technology, complicated navigation systems such as inertial navigation system and global positioning system have been employed. These navigation systems have their own strengths and weaknesses. To improve overall system performance they are integrated together as one system.
Presented research aims at developing the integrated navigation system through particle filters. In this study, after a brief overview of the data integration techniques, several techniques which are more common and have better performance than others are examined. This contribution concentrates on filtering methods... 

In this document, the cooperative estimation of states between two interceptors and one target is expressed in order to evaluate the effect of information sharing in different situations on the estimation performance. Due to the importance of the proper estimation of the target acceleration in advanced navigation rules, the main focus of the document is on a more precise estimation of the absolute states of the target. For this purpose, a filter based on the extended Kalman filter was used as an estimator, and to evaluate the promotion of the estimation performance, the combination of measured data was used in two different ways. Matlab Simulink is the simulation software used. The dynamics... 

This thesis deals with the attitude estimation based on low cost sensor for a micro satellite in a circular, low earth orbit (LEO) and sensor calibration. With two body problem theory and Quaternion formulation, rotational motion is modeled. In addition gravity gradient effect is considered on satellite orbital elements. Using a 3-axis MEMS-based magnetometer and a sun sensor as two measurement systems, low cost attitude estimation is proposed. Bias and Scale factor are presented to model deterministic sensor error and white Gaussian noise to model stochastic sensor error. It is shown that by sensor calibration the estimation accuracy will improve. Non-linear estimation methods EKF, SRUKF... 

In this thesis, autonomous orbit estimation of regional navigation satellites has been investigated. Estimation of satellite orbit is an integral part of satellite navigation, which may be executed via assistance of ground station. As the satellite is exposed to the ground station view, range, direction and rate of range is measured by mean of ranging instrumentation relative to ground reference, hence the precise position is calculated. In this thesis a set of satellites are investigated in a unique structure called constellation with the purpose of navigation. The occurrence which is likely to happen in this condition, is the failure of ground station under certain circumstances or losing... 

This paper proposes a novel probabilistic framework for output-only identification of a soil-structure system. The system is modeled by a vertical shear beam resting on the soil representative springs. The proposed framework estimates the unknown parameters of the system and the foundation input motion time history simultaneously, using sparsely measured responses of the structure. The unknown parameters of the system include stiffness of the sway and rocking springs, shear modulus of the beam, and the modal damping ratios of the system. These parameters are modeled as random variables whose joint probability distribution is updated in a Bayesian scheme using the observations of structural... 

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... 

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,... 

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... 

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... 

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... 

With confidence in the recorded observations, the RLS method no longer estimates the recorded measurements by sensors, i.e. the displacement and speed of the floors, and only estimates the parameters. In contrast, in the EKF method, in addition to estimating the structure's parameters, a more precise estimation of the observations recorded by the sensors has been done by accepting the noise in the recorded observations. These methods, which are based on the Bayesian updating, investigate the two primary sources of uncertainty in a problem: a) measurement noise or observation noise, and b) process noise, which includes modeling errors. In these methodologies, the unknown system parameters,... 

Global climate change and anthropogenic impacts lead to alterations in the water cycle, water resource availability and the frequency and intensity of floods and droughts. As a result, developing effective techniques such as hydrological modeling is essential to monitor and predict water storage changes. However, inaccuracies and uncertainties in different aspects of modeling, due to simplification of meteorological physical processes, data limitations and inaccurate climate forcing data limit the reliability of hydrological models. Assimilation of new observations constrains the dynamics of the model based on uncertainties associated with model and data, which can introduce missing water... 

In this study, the cooperative inertial navigation systems are used to prevent the error growth of the inertial navigation system in unmanned aerial vehicles that fly in group. Here, the navigation problem is defined for a group of unmanned vehicles, flying with full six degrees of freedom and the objective is to estimate the navigation information of all cooperators. Due to the nonlinear equations, the decentralized extended Kalman filter is used to estimate the states of the system. This means that there is a Kalman filter in each vehicle. The inputs of this filter are the range and the bearing angles between the vehicle and the cooperators, the estimated position of the cooperators and... 

This dissertation presents a comprehensive probabilistic framework based on system identification for rapid seismic damage assessment of buildings at regional scale. Given the large number of buildings within a region and the need for rapid damage detection, this research uses simplified models with low computational cost to model each building. For this purpose, stochastic filters are employed as system identification tools. In the first step, a continuous linear model consisting of a Timoshenko beam in combination with the extended Kalman filter is utilized. This model is subjected to joint state-parameter identification under both fixed- and flexible-base conditions. Additionally, the... 

In this paper, an approach is proposed to estimate the location of the leaks in oil pipelines. The pipeline possesses a system of Partial Differential Equations (PDE). First, a closed-form solution is applied to the pipeline equations and the leakage location is found solving the steady-state equations. To tackle the case where the pressure and flowrate do not reach constant values, the initial estimations are provided by the closed-form solution. Then, the pressures, flow rates, and leakage coefficient are estimated by solving the system of differential equations. This system is then discretized with respect to the location variable to yield the system state equations which, in turn, are... 

One of the main challenges in managing flow batteries usage is estimating their state of charge. Since The concentration of ions in the battery indicates the battery's charge and, on the other hand, the sensors for measuring the concentration are expensive, observers should be used to estimate the concentrations of the ions in the battery. This work is done by measuring the cell voltage, and finally, using the mathematical model of the battery, the amount of concentrations and state of charge is calculated. In this work, a vanadium flow battery was initially modeled accurately and mechanistically using COMSOL software to replace an actual flow battery in subsequent studies. Also, two... 

In this thesis, in order to improve the performance of the mobile robot navigation, a Fuzzy approach is used for making a safe path in the cluttered environment with hurdles in the work space of the robot. To this end, based on data collected from instantaneous location of the robot and location of the robot, heuristic rules are extracted. Also, in order to obtain optimal data fusion of the sensors, Kalman filter is used to localize the robot. In this regards, by using the kinematics of the robot and supposing the white noise in the process and measurements, the position and orientation of the mobile robot are estimated in a real-time and adaptive manner  

Simulation of cardiovascular system functionality during various physiological conditions is essential at different diagnostic and clinical levels. A first step in studying the roots of cardiovascular diseases and abnormal activity is to study a practical yet complete model of the cardiovascular system. In this thesis we introduced a new approach for defining the distributed model of the cardiovascular system. Initially, we chose an appropriate subsystem, namely Arch of Aorta, and proposed a distributed model for it. The elements of the proposed model were nonlinear RLC elements that simulate resistance, blood viscosity and vessel elasticity respectively. To minimize the system complexity,... 

Nonlinear nature of polymerization reactors has always attracted great attentions in various scientific areas such as modeling, simulation, dynamical behavior investigation and control engineering as well. Free radical polymerization in continuous reactors, whether in terms of design and startup or in terms of economical concerns, has numerous fans in industrial aspects. In the following thesis, the dynamical behavior of continuous stirred tank reactor of Vinyl Acetate free radical polymerization is examined in an industrial scale. A control system with optimum performance is designed for this CSTR as well. According to the common behavior of this type of reactor, it may demonstrate...