Sharif Digital Repository

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 study is an attempt to investigate and analyze uncertainty through the Glue method in parts of Tabriz, Iran, using the SWMM urban flood model. In order to quantify the uncertainty, the initial range of input parameters including curve number, impenetrability percentage, penetrability level’s coarseness coefficient, and impenetrability level’s coarseness coefficient are defined and the GLUE algorithm is used to conduct primary sampling operation from parametric space using Latin hypercube sampling method. Considering the simulation results and the observed values of synchronized events, about %20 of the total outputs and generated parameters series have been excluded as acceptable... 

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... 

Hepatitis is one of the most perilous viral infectious diseases and many people suffer from it all around the world. In particular, hepatitis B is a terribly dangerous disease which may cause severe liver damage or cancer if it is not treated. Recently, several dynamic models have been developed from experimental studies for describing such diseases mathematically. The certainty of these dynamics models is questionable in realistic treatment processes. Thus, the modeling uncertainties should be considered in the dynamics, which necessitates employing robust control strategies capable to overcome these uncertainties. Accordingly, in this research, a control strategy is developed in order to... 

A new procedure is proposed to quantify uncertainties involved in the seismic response of structures including ground motion and modeling variability. The advent of performance-based earthquake engineering (PBEE) and probabilistic seismic risk analysis necessitates consideration of uncertainties in predicting seismic responses. However, the high computational cost of conventional methods restricts their application to only simple numerical models. The present study employs the endurance time (ET) method concept to predict the response distribution which requires much less computational efforts than conventional methods. The proposed procedure for the quantification of record-to-record... 

This paper presents a new set of reliability sensitivity measures. The purpose is to identify the optimal manner in which to mitigate risk to civil infrastructure, and reduce model uncertainty in order to improve risk estimates. Three measures are presented. One identifies the infrastructure components that should be prioritized for retrofit. Another measure identifies the infrastructure that should be prioritized for more refined modeling. The third measure identifies the models that should be prioritized in research to improve models, for example by gathering new data. The developments are presented in the context of a region with 622 buildings that are subjected to seismicity from several... 

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... 

The present work addresses chaos synchronization between two different general chaotic systems with parametric and structural uncertainties, subject to external disturbances and input dead-zone nonlinearities. In this regard, a novel robust controller has been designed that guarantees asymptotic stability of synchronization errors and boundedness of all closed-loop signals. One advantage of the proposed controller over the existing control algorithms is using only one update law for estimating the structural uncertainties, external disturbances, and unknown characteristics of the dead-zone nonlinearities, which reduces the computational burden considerably. The designed controller is... 

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... 

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... 

We present a geometric approach for fault detection and isolation (FDI) in robotic manipulators in presence of model uncertainty. A systematic procedure is introduced for representing robotic system model being affine with respect to faults and disturbances. The proposed residual generator has smooth dynamics with freely selectable functions and it does not require high gains or threshold adjustment for the FDI purpose. No assumption on amplitude of faults and their rate is used. The solvability conditions for the FDI problem lead to a quotient observable subspace unaffected by all unknown inputs except the faults. Simulation example demonstrates localization of faults in presence of... 

Under different loading conditions, the over-head cranes may experience a wide range of model parameters variation. A robust control strategy is developed to achieve the high positioning accuracy, short transportation time and suppression of swing angle for an uncertain over-head crane system. Over-head crane is modeled as a three degrees of freedom system and control problem is investigated for two cases: a system with a single control input (the force on trolley) and a system with two control inputs (the force on trolley and the torque on lifter). Regulator and observer systems are designed. To achieve the tracking objectives, an optimal robust controller is designed based on μ-synthesis... 

In mechanical assemblies, individual components are placed together to deliver a certain function. The performance, quality, and cost of the mechanical assembly are significantly affected by its tolerances. Toleranced dimensions inherently generate an uncertain environment in a mechanical assembly. This paper presents a proper method for tolerance analysis of mechanical assemblies with asymmetric tolerances based on an uncertainty model. This mathematical approach is based on fuzzy logic and tolerance accumulation models such as worst-case and root-sum-square methods. A fuzzy-based tolerance representation is developed to model uncertainty of tolerance components in the mechanical... 

Under different loading conditions, the over-head cranes may experience a wide range of model parameters variation. A robust control strategy is developed to achieve the high positioning accuracy, short transportation time and suppression of swing angle for an uncertain over-head crane system. Over-head crane is modeled as a three degrees of freedom system and control problem is investigated for two cases: a system with a single control input (the force on trolley) and a system with two control inputs (the force on trolley and the torque on lifter). Regulator and observer systems are designed. To achieve the tracking objectives, an optimal robust controller is designed based on μ-synthesis... 

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... 

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... 

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  

This study presents a framework that utilizes Bayesian regression to create probabilistic cost models for retrofit actions. Performance improvement is the key parameter introduced in the proposed framework. The incorporation of this novel feature facilitates the characterization of retrofit cost as a continuous function of the desired performance improvement. Accounting for the performance gained from retrofit enables the use of the models in determining the optimal level of retrofit. Furthermore, accounting for the model uncertainty facilitates the use of the models in risk and reliability analyses. The proposed framework is applied to create seismic retrofit cost models for masonry school...