Sharif Digital Repository

Accurate and fast attitude estimation of a rigid body plays an essential role in the performance of a vehicle’s control system, especially aerospace vehicles. Ample works have been done to increase the accuracy and speed of the attitude estimation process, but all have been developed according to a model-based approach. This approach assumes that the torques acting on the body have a known dynamical model that is used for the attitude estimation. The purpose of the present research is to estimate the attitude via a model-free approach, i. e. dynamics of the torques acting on the body are no longer assumed to be known, and its learning is the next step. Thus, the problem formulation of this... 

In this research, the aim is to investigate the use of data assimilation method for better reservoir model updating in the reservoir management. In addition, multi-objective optimization concept is studied for the production optimization. The application of these methods is applied for reservoir management in the naturally fractured reservoirs. To update the reservoir, ensemble based methods, especially ensemble Kalman filter and ensemble smoother, are used. To tackle the challenges encountered with these methods, modifications are proposed to obtain a better history matching and more accurate reservoir characterization. The proposed framework for history matching is implemented for the... 

In many fields, due to the lack of thickness of the reservoir layer, vertical drilling cannot be used due to low wellbore efficiency, so to solve this problem, directional and horizontal drilling is used. During drilling of highly deviated wells, to increase the efficiency of directional drilling, it should be tried to keep the path of the well completely in the reservoir layer, so that the full capacity of this type of drilling is used and the efficiency of the well is increased. To achieve this goal, Geo-Steer drilling technology is proposed in which decisions on the path of the well are made with the help of current reservoir and geological data. In this type of drilling, instantaneous... 

Inspection of confined corridors is one of the important and necessary topics in various industries, including mines, oil and gas industries. Human inspection is very time-consuming and expensive due to the difficulty of accessing these environment, and in some corridors, it is not possible to inspect at all. In this thesis, UAV guidance and navigation algorithms have been developed by using informations got from optical flow, inertial and ultrasonic sensors, so that the UAV can fly automatically inside the confined corridor without colliding the boundaries. At first, a model of the space around the corridor, UAV and its subsystems has been proposed so that we can use it to create a... 

Nowadays, horizontal drill string is a powerful tool for drilling in the oil and gas industry and an efficient method for constructing underground tunnels in cities. Despite its many uses, this method is exclusive to limited countries and is considered among the most advanced methods for drilling. One of the most important problems in the field of horizontal drilling is the existence of destructive axial, torsional and lateral vibrations. If these vibrations are not controlled, they can cause irreparable damage to the plant and drilling well. Among the introduced vibrations, axial and torsional vibrations have a very dominant effect on the drilling process, so the purpose of this research is... 

Adverse social and economic effects of earthquakes have necessitated the emergence and development of efficient methods to assess and monitor the health status of structures. Many of the structural health monitoring algorithms are based on linear models that are not able to provide sufficient dynamic information. Nonlinear models require monitoring of a larger number of structural parameters and provide a much closer to reality model of the structure. Therefore, the use of nonlinear models in the identification process provides more useful information about the safety and serviceability of post-earthquake structures. Also, most of the existing methods are not applicable for online health... 

Algorithms for online identification of parameters of a satellite’s moment of inertia tensor based on two methods (recursive least squares and Kalman Filter) is presented and compared with each other. It is assumed that the satellite actuators are three orthogonal reaction wheels. The only available sensor is a 3-axis rate gyro, which measures the angular velocity of satellite in body coordinate system. For validation of algorithms on earth, a similar identifier was designed for a satellite simulator. Due to difference in Dynamics of satellite and satellite simulator, capability of identifying center of gravity was added to algorithms. In order to account for friction in air bearing of... 

The study of nonlinear systems estimation techniques is necessary due to radar measurement equations which commonly contain range and angle, nonlinearly related to motion state variables.Hence in this thesis we make a through study of various nonlinear estimation techniques and important dynamic modelsfor airborne maneuvering and ballistic targets. Then we represent a novel method based on nonlinear vector transformation which tries to improve common nonlinear estimation techniques.Two Algorithms, DBF and MBF, baesd on data fusion is proposed to fuse a model data and also various models abilities in a separate chapter.Finally several estimator filters are simulated and analysed for two... 

In thisstudy, a three-dimensional modelbased onpartial differential equations (PDEs) was used foraplanarsolid oxidefuel cellunit. These PDEs were evaluatedregardingthe equations ofconservation involvingelectric, ionic charge, mass,energy andmomentum equilibriums.To investigate the behavior and strength of the presented model, thestatic and dynamic analyses were considered. The trend of the system against thechanges incurrent density, flow rateand fuelflow ratewere investigated.The PDE of the real model evaluated using the finite element method inCOMSOLsoftware and The PDE of the EstimatorisimplementedinMATLABenvironment by orthogonalcollocation method.Kalman Nonlinearobserverto estimate... 

In this thesis a dynamical model is introduced for Phonocardiogram based on its morphology which is capable of generating synthetic signals with realistic morphology. The model is for normal Phonocardiograms which includes the two dominant heart sounds, namely the first and the second sounds, and is inspired by the Electrocardiogram dynamical model. In the proposed dynamical model each heart sound is modeled with several Gabor kernels. The ultimate goal of such dynamical model is to establish a model-based processing framework for Phonocardiogram. This framework is devised by employing the dynamical model equations within an Extended Kalman Filter structure, and the simultaneously recorded... 

Cardiovascular diseases are one of the major causes of mortality in humans. One way to diagnose heart diseases and abnormalities is processing of cardiac signals such as ECG.In many of these processes, inter-beat and intra-beat features of ECG signal must be extracted. These features include peak, onset and offset of ECG waves,meaningful intervals and segments that can be defined for ECG signal. ECG fiducial point (FP) extraction refers to identifying the location of the peak as well as the onset and offset of the P-wave,QRS complex and T-wave which convey clinically useful information. However, the precise segmentation of each ECG beat is a difficult task, even for experienced... 

In this work, a non-isothermal model of natural gas in pipelines including mass, momentum and energy balance equations are used as model equations for modeling and state estimation in gas pipeline systems. An algorithm is proposed to handle the discontinuities that appear in the dynamic model of a GTN. The states of GTN are estimated using the continuous/discrete form of the extended Kalman filter for two benchmarks and some heuristic rules for sensor placement in a GTN are concluded. Also, a framework for distributed and decentralized state estimation in high-pressure and long-distance gas transmission networks (GTNs) is proposed. Some heuristic rules are suggested for system decomposition... 

State estimation is a process in which values of unknown system state variables is obtained by considering measurements in such a system. State estimators’ output data are applied in control centers of power systems. Nowadays, using of phasor measurement unit (PMU) in WAMS (Wide Area Measurement Systems) and SCADA have significantly extended. PMUs increase the accuracy proportion compared with traditional measurement units, improve the power networks observability as well as detect and correct bad data. Since the possibility of removing the traditional measurement devices and replacing them with full PMU ones does not exist in the near future it is mandatory to find out an efficient and... 

Unscented kalman filter is able to integrate strapdown inertial navigation system (SINS) and celestial navigation system (CNS) and estimate current attitude and gyro drift precisely. However, initial attitude error, accelerometer bias and attitude error caused by gyro drift prior to CNS setting to work may cause large errors in velocity and position. So a novel method is presented for compensating these errors. The proposed method implements Fixed-interval smoothing to the integrated system. The procedure of filtering, smoothing and accelerometer bias estimation has been explained in details. The validity of the designed method has been proved through a simulation which admits the capability... 

One of the major problems encountered in artificial intelligence is environment interaction. A sensible way for around-interaction is to collect information from sensors and make proper reactions. Generally, in the real world, an intelligent agent needs to know its pose. There are several ways to know the pose of an agent. One of them is based on the fusion of the output of an inertial sensor with the information retrieved from a camera. This leads to enhance the estimation of the pose of an agent. In this research different solutions for this problem are compared. Studies are done with the goal of attitude detection for vehicles and mini-robots, moving on planar surface. For this end, we... 

Management decisions, enhanced oil recovery, and reservoir development plans in petroleum industries are based on predictions by reservoir simulation. Due to uncertainties in model parameters or engineering assumptions, the simulation results are not accurate, while they are correct. For more accurate estimation of unknown production quantities, it is required to characterize the unknown parameters and its uncertainty. By using static data alone the result of characterization is unreliable and unsure, therefore dynamic data use practically. In reservoir engineering literature, this is called “History Matching”.The ensemble Kalman filter is an optimal recursive data processing algorithm based... 

Inertial motion capture systems widely use low-cost IMUs to obtain the orientation of human body segments, but these sensors alone are unable to estimate link positions. Therefore, this research used a SLAM method in conjunction with inertial data fusion to estimate link positions. SLAM is a method that tracks a target in a reconstructed map of the environment using a camera. This paper proposes quaternion-based extended and square-root unscented Kalman filters (EKF & SRUKF) algorithms for pose estimation. The Kalman filters use measurements based on SLAM position data, multi-link biomechanical constraints, and vertical referencing to correct errors. In addition to the sensor biases, the...