Sharif Digital Repository

A new time-domain hierarchical Bayesian framework is proposed to improve the performance of Bayesian methods in terms of reliability and robustness of estimates particularly for uncertainty quantification and propagation in structural dynamics. The proposed framework provides a reliable approach to account for the variability of the inference results observed when using different data sets. The proposed formulation is compared with a state-of-the-art Bayesian approach using numerical and experimental examples. The results indicate that the hierarchical Bayesian framework provides a more realistic account of the uncertainties, whereas the non-hierarchical Bayesian approach severely... 

The present study is set out to systematically investigate the combined impact of operational, geometrical, and model uncertainties on the hemodynamics and performance characteristics in the U.S. Food and Drug Administration (FDA) benchmark centrifugal blood pump. Non-intrusive Polynomial Chaos Expansion (NIPCE) has been utilized to propagate the uncertainty of 12 random input variables in the flow field and the performance characteristics of the blood pump at three working conditions. The global sensitivity of the Quantities of Interest (QoI) to the uncertain input parameters was measured through the Sobol’ indices. The Multiple Reference Frames (MRF) approach and the SST k−ω turbulence... 

Recent progress in developing artificial neural network (ANN) metamodels has paved the way for reliable use of these models in the prediction of air pollutant concentrations in urban atmosphere. However, improvement of prediction performance, proper selection of input parameters and model architecture, and quantification of model uncertainties remain key challenges to their practical use. This study has three main objectives: to select an ensemble of input parameters for ANN metamodels consisting of meteorological variables that are predictable by conventional weather forecast models and variables that properly describe the complex nature of pollutant source conditions in a major city, to... 

In this paper, an approach to physical collaboration between a patient and a therapist is proposed using a bilateral impedance control strategy developed for delayed tele-robotic systems. The patient performs a tele-rehabilitation task in a resistive virtual environment with the help of online assistive forces from the therapist being provided through teleoperation. Using this strategy, the patient's involuntary hand tremors can be filtered out and the effort of severely impaired patients can be amplified in order to facilitate their early engagement in physical tasks. The response of the first desired impedance model is tracked by the master robot (interacting with the patient), and the... 

Mechanistic modelling is an engineering approach to simulate reasonable physical and chemical processes to develop a model to describe the behaviour of a system. Mathematical models are commonly adopted to explore the physical limits of a process, and are applied to process development, optimization and control. In this work, the population balance model and the moment technique have been utilized to model a suspension polymerization reactor and predict the dynamic evolution of particle size and molecular weight distributions. These distributions are two important factors that affect the physical, rheological and mechanical properties of a polymer, and its final product quality. The cell... 

In this paper, a nonlinear robust adaptive sliding mode control strategy is presented for the influenza epidemics in the presence of model uncertainties. The nonlinear epidemiological model of influenza with five state variables (the numbers of susceptible, exposed, infected, asymptomatic and recovered individuals) and two control inputs (vaccination and antiviral treatment) is considered. The objective of the proposed controller is decreasing the number of susceptible and infected humans to zero by tracking the desired scenarios. As a result of this decreasing, the number of exposed and asymptomatic individuals is also decreased and converged to the zero. Accordingly, it is shown that the... 

In this paper, a nonlinear adaptive control method is presented for the treatment of the Hepatitis B Virus (HBV) infection. Nonlinear dynamics of the HBV, modeling uncertainties and three state variables (the numbers of uninfected and infected cells and free viruses) are taken into account. The proposed control law is designed for the antiviral drug input such that the number of free viruses and consequently the number of infected cells decrease to the desired values. An adaptation law is also presented to overcome modeling uncertainties by updating estimations of the system parameters during the treatment period. The stability of the process and convergence to desired state values are... 

Efficient robust control methods are required to keep the boiler-turbine unit performance appropriately. In this paper, a hybrid multivariable robust control strategy including the regulator and observer is designed to improve the performance of an industrial boiler-turbine unit. In the nonlinear model of the process, output variables including the drum pressure, electric power and water level of the drum are controlled at the desired set-points by manipulation of the fuel, steam, and feed-water flow rates. Due to economic and technical reasons and for the estimation of process states, the full-order observer is designed. For disturbance rejection and process stability, a regulator system is... 

The flight of unmanned aerial vehicles is often associated with model uncertainties, measurement noises, and environmental disturbances such as wind gust. To mitigate these challenges, the accurate estimation of states is vital. Moreover, the wind model and its parameters should also be estimated and compensated during the flight. In this paper, a multiple model filter is implemented for this purpose. To investigate the performance of the multiple model filter, three different models including constant wind, '1-cosine' model and wind shear model are considered. The multiple model filter utilizes three extended Kalman filter to simultaneously estimate the model of wind, the parameters of the... 

One of the best ways to control water shortages in the central region of Iran is Inter-Basin Water Transfer (IBWT). Efficient decision making on this subject is, however, a real challenge for the water authorities in Iran. These decisions should include multiple attributes, model uncertainty and, also, the optimistic/pessimistic view of the decision makers. The Ordered Weighted Averaging (OWA) operator can be used as an efficient Multi-Attribute Decision Making (MADM) method. This paper will introduce a new method to obtain the order weights of this operator. The new method is based on a combination of fuzzy quantifiers and neat OWA operators. Fuzzy quantifiers are usually applied in soft... 

A new nonlinear model reference adaptive impedance controller is presented for the control of robot manipulators with uncertainties in model parameters such as friction coefficients. This method provides asymptotic tracking of a reference impedance model for the robot end-effector in operational space which is more sensible for the patient compared to the joint space impedance used in previous works. The model uncertainties such as friction coefficients are compensated using an adaptation law. The asymptotic tracking of the reference impedance model is shown using a Lyapunov function. The tracking performance and friction compensation are also demonstrated through simulation on a... 

One of the most important phenomena to affect the motion behaviour of Micro Resonators is their thermal dependency. This has recently received the attention of researchers widely. A thermal phenomenon has two main effects, the first is damping, due to internal friction, and the second is softening, due to Young's modulus-temperature relationship. In this research work, some theoretical and experimental reported results are used to make a proper model, including thermal phenomena. Two Lorentzian functions are used to describe the restoring and damping forces caused by thermal phenomena. In order to emphasize the thermal effects, a nonlinear model of the MEMS, considering capacitor... 

In this paper, we address recovery of sparse signals from compressed measurements, and sparse signal approximation, which have received considerable attention over the last decade. First, we revisit smoothed L0 (SL0), a well-known sparse recovery algorithm, and give some insights into it that have not been noticed previously. Specifically, we re-derive the SL0 algorithm based on proximal methods, and using recent results in solving nonconvex problems by proximal algorithms, we provide a convergence guarantee for it. In addition, inspired by this derivation, we propose a general family of algorithms, which we call iterative sparsification-projection (ISP), having SL0 as a special member. Our... 

In-flight aircraft center of gravity (COG) position estimation is investigated in this study based on the kinematics approach. The Quad-M basics of system identification requirements are carefully investigated for time-invariant and time-varying COG estimation during airdrop maneuver as a case study that contains both conditions. Modeling and simulation of airdrop maneuver are employed to prepare the required maneuver and measurement data for this investigation. The relative-acceleration equation, as a model structure, and parameter modeling of time-varying COG location and acceleration are introduced into the system identification and parameter estimation framework. The Kalman filter method... 

During drying processes, moisture control of food products, such as dried tea, is of great importance. Improving dryer control, results in consistent production and reduction of energy consumption. However, the dryer is a complex system associated with model uncertainties. In this paper, a realistic uncertain model of a fluidized tea bed dryer is considered. Moisture content and temperature of tea leaves (or other products) are controlled at desired values by manipulating tea leaves heating rate. Developing a code by Robust Control Toolbox of MATLAB and modeling uncertainties, a robust controller is designed based on ′-synthesis with DK-iteration algorithm. Results show that in the presence... 

Recent developments in the space industry and the great tendency to define efficient, precise and low cost missions are the main reasons for the growing interest in satellites formation flight. Regarding the aforementioned, the study of multiple satellites control methods is the subject of the present paper. In this paper, two linear robust control strategies are applied to position control system of certain satellites in the virtual structure formation flight. The proposed controllers are designed considering different parametric uncertainties such as semimajor axis and eccentricity changes as well as some disturbances like second term of gravitational acceleration function (j2) and drag... 

This paper presents a hierarchical Bayesian modeling framework for the uncertainty quantification in modal identification of linear dynamical systems using multiple vibration data sets. This novel framework integrates the state-of-the-art Bayesian formulations into a hierarchical setting aiming to capture both the identification precision and the variability prompted due to modeling errors. Such developments have been absent from the modal identification literature, sustained as a long-standing problem at the research spotlight. Central to this framework is a Gaussian hyper probability model, whose mean and covariance matrix are unknown, encapsulating the uncertainty of the modal parameters.... 

Dynamic thermal rating (DTR) of transmission system facilities is a way to maximally realize the equipment capacities while not threatening their health. With regards to transmission lines, the allowable current of conductors is forecasted based on the environmental situations expected in some forthcoming time periods. Due to the fact that weather conditions continuously vary, sampling points are very limited against many line spans, and the measurements have an inherent error, uncertainties must be appropriately included in the DTR determination. This paper adopts the fuzzy theory as a strong and simple tool to model uncertainties in the DTR calculation. Since DTR intends to determine the... 

This paper is a counterfactual analysis investigating the consequences of the formation of a currency union for Canada and the USA: whether outputs increase and prices decrease if these countries form a currency union. We use a two-country cointegrated model to conduct the counterfactual analysis, where the conditional forecasts are generated based on the Gaussian assumption. To deal with structural breaks and model uncertainty, conditional forecasts are generated from different models/estimation windows and the model-averaging technique is used to combine the forecasts. We also examine the robustness of our results to parameter uncertainty using the wild bootstrap method. The results show... 

In this paper, we introduce a new approach to fault detection and isolation for robot manipulators. Our technique is based on using a new simplified Euler-Lagrange (EL) equation that reduces complexity of the proposed fault detection method. The proposed approach isolates the faults and is capable of handling the uncertainty in manipulator gravity vector. It is shown that the effect of uncalibrated torque sensor measurement is asymptotically rejected in the detection process. A simulation example is presented to illustrate the results. © 2009 IEEE