Sharif Digital Repository

The battery management system (BMS) in electric vehicles monitors the state of charge (SOC) and state of health (SOH) of lithium-ion battery by controlling transient parameters such as voltage, current, and temperature prevents the battery from operating outside the optimal operating range. The main feature of the battery management system is the correct estimation of the SOC in the broad range of vehicle navigation. In this paper, to estimate real-time of SOC in lithium-ion batteries and overcome faults of Extended Kalman Filter (EKF), the Square-Root Sigma Point Kalman Filter is applied on the basis of numerical approximations rather than analytical methods of EKF. For this purpose, the... 

In this article, time-varying formation tracking problem for multi-agent systems is investigated. It is assumed the number of agents is changing and obstacles should be avoided along the trajectory. In addition, the tracking formation should be reached while the leader trajectory is unknown and communication data are noisy. To reach the desired formation tracking, first, a virtual leader is constructed using the local neighbouring data. Second, the reference signal is created based on the virtual leader and the leader data (which is available for some agents). The data fusion at this stage is done based on Kalman filtering to reduce the effect of communication noise. Third, an integral state... 

Sliding innovation filter (SIF) has recently been introduced as a robust strategy for estimation of linear systems. The SIF has been extended to nonlinear systems via analytical linearization. However, as the performance of the extended SIF (ESIF) degrades in the presence of severe nonlinearities, this article has initially developed a derivative-free cubature SIF (CSIF) that uses statistical linearization for the error propagation. In addition, the SIF gain has been reformed to incorporate the innovation covariance matrix, thus reducing the estimation error. Furthermore, the adaptive fading factor has been employed to strengthen the robustness and convergence properties of the CSIF against... 

Registration is the most consequential topic to be dealt with in a multi-sensor tracking system. On the other hand, providing satisfactory target acceleration estimation would enhance the performance of a ground-based air defense system encountering a maneuvering target. The main novelty of the present work is addressing a new scheme to solve the registration problem in a distributed network along with estimating accurate target acceleration, simultaneously. The details of coping with three common kinds of measurement, attitude, and location biases are explored concentrating on the effects of attitude bias as the main error source from the practical viewpoint. A modified iterated extended... 

Battery energy systems are playing significant roles in smart homes, e.g., absorbing the uncertainty of solar energy from root-top photovoltaic, supplying energy during a power outage, and responding to dynamic electricity prices. For the safe and economic operation of batteries, an optimal battery-management system (BMS) is required. One of the most important features of a BMS is state-of-charge (SoC) estimation. This article presents a robust central-difference Kalman filter (CDKF) method for the SoC estimation of on-site lithium-ion batteries in smart homes. The state-space equations of the battery are derived based on the equivalent circuit model. The battery model includes two RC... 

In this paper, a novel scheme of command to line-of-sight guidance law regarding the outstanding practical limitations is proposed. With the aid of formulating problem in pursuer's line of sight frame, the exact feed-forward acceleration commands are derived for a general target motion in three-dimensional engagement geometry. Then, a nonlinear control scheme constructed from feed-forward terms along with a nested saturated feedback strategy is suggested. Two momentous practical limitations are considered. The first is related to existence of pursuer's acceleration saturation which is ignored in all existing solutions. The required conditions to insure the global stability are derived... 

Nowadays, Autonomous Underwater Vehicles (AUV) are used in environmental studies, ocean floor mapping, and measuring water properties. Navigation of these vehicles is one of the most challenging issues due to the unavailability of global positioning system (GPS) signal underwater. Inertial navigation is a method commonly used for underwater navigation. If a low-cost Inertial Measurement Unit (IMU) is used, navigation quality will decline rapidly due to sensor inherent error. Although using a Doppler Velocity Log (DVL) speedometer sensor helps limit this error to some extent, it does not yield acceptable accuracy in low-cost IMUs. Filtering the gyro based on the AUV rotational dynamics model... 

Spreading Covid19 has significantly impacted humans' affairs worldwide, either economically or in a sanitary manner. Besides social distance and hospitalization, making and introducing different vaccines help us ameliorate infection and mortality rates. In this research, we use a nonlinear dynamic model for Covid19, with eight states named susceptible, exposed, infected, quarantined, hospitalized, recovered, deceased, and insusceptible populations. Also, we use social distancing, hospitalization, and vaccination rate as three control inputs. This research aims to stop the Covid-19 from spreading worldwide and minimize exposed, infected and deceased populations using model predictive control.... 

The navigation algorithms which use inertial measurement units (IMUs), such as inertial navigation systems (INSs), always suffer from intrinsic accumulated errors. Bias in gyros induces a significant drift in navigation output especially when micro-electro-mechanical sensor (MEMS) type is used. This error has high-and low-frequency components. De-noising of the long-term error (LTE) (the low-frequency component) is more challenging due to undeterministic behavior and overlapping with carrier motion in the low-frequency band. In this article, a method for de-noising of long-term MEMS-based gyro is presented. In this approach, an auto-regressive (AR) model for the LTE is developed which is... 

Solar panel flexibility plays an important role in the attitude control of satellites. Therefore, traditionally the deformations of flexible solar panels are measured with a series of sensors along the panels itself. This paper presents a novel maiden attempt to simultaneously estimate the attitude and deformation of a flexible satellite using only 2 low-cost attitude sensors namely the sun sensor and magnetometer measurements. The flexible satellite is considered as a central rigid body with two attached flexible panels in order to derive the governing dynamic equations based on the Lagrange's equation. Both Extended Kalman filter (EKF) and Unscented Kalman Filter (UKF) are employed for the... 

A modified unscented Kalman filter is presented to estimate the quaternion parameters as well as the angular velocities of a rigid gyro-less satellite under faulty sensor conditions. The task is carried out using the Sun sensor and magnetometers as attitude sensors with bounded noise and unknown fault(s). Following the presentation of the satellite attitude dynamics and filtering formulations, a new fault detection and isolation algorithm is proposed. The latter is based on a modified unscented Kalman filter structure for improved fault detection, sensor isolation, and attitude control (AC). A Backtracking Search Algorithm (BSA) is also used to design and optimize the PID controller gains,... 

In this paper, the drivetrain identification problem of a horizontal axis gear-driven wind turbine has been considered. The identification problem leads to a precise model of the drivetrain of the wind turbines which plays a key role in the production and transmission of electrical energy. This process consists of two stages: First, offline identification which needs the input–output data from the drivetrain system. These data are obtained from the FAST code. FAST (Fatigue, Aerodynamics, Structures, and Turbulence) is a valid aeroelastic code in the simulation aeroelastic field of offshore and onshore wind turbines. In region 2 (wind velocity is between the cut-in and rated velocities), the... 

This study presents a novel method for observation of stage position in a 2D nano-positioning system based on a hybrid Kalman filter. The proposed method obviates the need to measure the stage position directly using complex and costly capacity sensors. Instead, traditional piezo actuators equipped with strain gauge sensors are utilized to measure the deection of the magnification system at the position of actuators. Then, a powerful estimation algorithm called Kalman filter was employed to observe stage displacements. The designed hybrid Kalman filter uses dynamical equations of motion in the prediction step. The piezo actuators deections are measured and exploited to correct the predicted... 

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 paper, 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 model,... 

Unlike a single-body approach, modeling based on a two-body approach has been employed to prepare the required system dynamic model as a time update equation in the applied filtering technology and measurement data for the estimation process. This more precise mathematical model enabled better understanding about the dynamics of the change in the aircraft mass properties during the airdropping operation. The problem is defined as estimation of the optimal mass properties parameters for the best possible fit of the model output to the real data. The parameter estimation problem is investigated by a nonlinear filtering methodology in two sequential steps. In the first step, the single extended... 

This study introduces a novel Bayesian framework for online and real-time vibration control of beam type structures, which represent a comprehensive control system associated with input-state algorithms. Control design systems typically require knowledge of system states, which in structures are displacements and velocities at some degrees of freedom. Currently, full-field measurements of displacements and velocities in large structural systems are not feasible. Also, properties of the moving inertial loads as key parameters in control designs are assumed known; however, in practice, measuring their characteristics is a challenging issue. As a remedy, an observer is required to estimate... 

Localization-capable inertial motion capture algorithms rely on zero-velocity updates (ZUPT), usually as measurements in a Kalman filtering scheme, for position and attitude error control. As ZUPTs are only applicable during the static phases a link goes through, estimation errors grow during dynamic ones. This error growth may somewhat be mitigated by imposing biomechanical constraints in multi-sensor systems. Error reduction is also possible by optimization-based methods that incorporate the dynamic and static constraints governing the system behavior over a period of time (e.g. the dynamic network algorithm); when this period includes multiple static phases for a link, its estimation... 

In this study, a real-time exible modular modeling approach to simulating the dynamic behavior of gas turbine engines based on nonlinear thermodynamic and dynamic laws is addressed. The introduced model, which is developed in the Matlab-Simulink environment, is an object-oriented high-speed real-time computer model and is capable of simulating the dynamic behavior of a broad group of gas turbine engines due to its modular structure. Moreover, a Kalman lter-based model tuning procedure is applied to decrease the modeling errors. Modeling errors are de ned as the mismatch between simulation results and available experimental data. This tuning procedure is an underdetermined estimation problem,... 

Motion capture is a process that movements of living organisms like human or objects are captured and the results are processed for the desired applications. These applications are in rehabilitation, sports, film industry and etc. There are many techniques and instruments for motion capture that optical camera systems are the most accurate ones. But these cameras are high cost and limited to labs. Some sensors like Inertial Measurement Units (IMU) and recently, Kinect cameras have been considered by many researchers because these are low cost and easy to use. But problems like bias, accumulated error and occlusion make them look for improvements. Fusion algorithms are one of the best methods... 

In this paper, a novel scheme of command to line-of-sight guidance law regarding the outstanding practical limitations is proposed. With the aid of formulating problem in pursuer's line of sight frame, the exact feed-forward acceleration commands are derived for a general target motion in three-dimensional engagement geometry. Then, a nonlinear control scheme constructed from feed-forward terms along with a nested saturated feedback strategy is suggested. Two momentous practical limitations are considered. The first is related to existence of pursuer's acceleration saturation which is ignored in all existing solutions. The required conditions to insure the global stability are derived...