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modeling-uncertainty
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A New Procedure for Derivation of Fragility Curve with Endurance Time Method
, M.Sc. Thesis Sharif University of Technology ; Estekanchi, Homayoon (Supervisor) ; Mahsuli, Mojtaba (Supervisor)
Abstract
This project aims at the calculation of response distribution of a structure using Endurance Time Analysis (ETA). The traditional approach for this calculation is Incremental Dynamic Analysis (IDA). One of the drawbacks of the IDA is its excessive computational complexity. In the ETA, the structure is analyzed using a set of artificial ground motions with increasing intensities as time passes. As a result, the ETA can be used to calculate the response distribution of the structure in a range of intensities. In the traditional ETA, only the median of the response is calculated. In this study, the response distribution is calculated as well as the median. To achieve this, the proposed approach...
Fragility and Risk Analysis of Electrical Substation Equipment Using Reliability and Endurance Time Methods
, M.Sc. Thesis Sharif University of Technology ; Esmail Pourestekanchi, Homayoon (Supervisor)
Abstract
Electrical substations and its vital components such as switchgears, have experienced severe damage during recent earthquakes, followed by widespread blackouts around the world. To improve the seismic resiliency of power grids and use probabilistic decision-making frameworks, comprehensive fragility data for the different equipment is needed. The purpose of this study is to assess the vulnerability of equipment in substations and to develop fragility curves for this equipment. For this purpose, four main equipment of switchgear, namely circuit breaker, disconnect switch, current transformer and surge arrester, have been modeled in three dimensions and verified. After examining the different...
Evaluating the uncertainty of urban flood model using glue approach
, Article Urban Water Journal ; Volume 19, Issue 6 , 2022 , Pages 600-615 ; 1573062X (ISSN) ; Fazloula, R ; Zarghami, M ; Akbarpour, A ; Sharif University of Technology
Taylor and Francis Ltd
2022
Abstract
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...
Optimal control of molecular weight and particle size distributions in a batch suspension polymerization reactor
, Article Iranian Polymer Journal (English Edition) ; Volume 28, Issue 9 , 2019 , Pages 735-745 ; 10261265 (ISSN) ; Shahrokhi, M ; Farahzadi, H ; Sharif University of Technology
Springer London
2019
Abstract
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...
Robust-fuzzy model for supplier selection under uncertainty: an application to the automobile industry
, Article Scientia Iranica ; Volume 25, Issue 4 , 2018 , Pages 2297-2311 ; 10263098 (ISSN) ; Modarres, M ; Azar, A ; Sharif University of Technology
Sharif University of Technology
2018
Abstract
This paper proposes an innovative robust-fuzzy method for multi-objective, multi-period supplier selection problem under multiple uncertainties. This approach integrates robust optimization and fuzzy programming. Uncertain parameters are modeled as random variables that take value within a symmetrical interval. However, due to the complexity or ambiguity of some real world problems and especially the nature of some of the available input data, the length of interval is also highly uncertain. This ambiguity motivated us to present a new approach, which could be applicable to multiple uncertainties conditions. Thus, in our approach, the half-length of these intervals is also represented by...
Adaptive synchronization of two different uncertain chaotic systems with unknown dead-zone input nonlinearities
, Article JVC/Journal of Vibration and Control ; Volume 26, Issue 21-22 , 2020 , Pages 1956-1968 ; Shahmoradi, S ; Shahrokhi, M ; Sharif University of Technology
SAGE Publications Inc
2020
Abstract
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...
A robust kalman filter-based approach for SoC estimation of lithium-ION batteries in smart homes
, Article Energies ; Volume 15, Issue 10 , 2022 ; 19961073 (ISSN) ; Habibifar, R ; Wang, Z ; Sharif University of Technology
MDPI
2022
Abstract
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...
Design of an RMPC with a time-varying terminal constraint set for tracking problem
, Article International Journal of Robust and Nonlinear Control ; Volume 26, Issue 12 , 2016 , Pages 2623-2642 ; 10498923 (ISSN) ; Haeri, M ; Sharif University of Technology
John Wiley and Sons Ltd
2016
Abstract
This paper presents a robust model predictive control algorithm with a time-varying terminal constraint set for systems with model uncertainty and input constraints. In this algorithm, the nonlinear system is approximated by a linear model where the approximation error is considered as an unstructured uncertainty that can be represented by a Lipschitz nonlinear function. A continuum of terminal constraint sets is constructed off-line, and robust stability is achieved on-line by using a variable control horizon. This approach significantly reduces the computational complexity. The proposed robust model predictive controller with a terminal constraint set is used in tracking set-points for...
Adaptive model predictive control-based attitude and trajectory tracking of a VTOL aircraft
, Article IET Control Theory and Applications ; Volume 12, Issue 15 , 2018 , Pages 2031-2042 ; 17518644 (ISSN) ; Rezaeizadeh, A ; Sharif University of Technology
Institution of Engineering and Technology
2018
Abstract
A novel adaptive model-based predictive controller for attitude and trajectory tracking of a vertical take-off and landing(VTOL) aircraft in the simultaneous presence of model uncertainties and external disturbances is introduced in this study. Animportant challenge of designing the model-based controllers is developing an accurate model, especially in the presence ofmodel uncertainties. In this study, first, the nominal model of a ducted-fan air vehicle, which is a multi-input multi-outputnonlinear system with non-minimum phase behaviour, is given as the test case of this research. After that, two modified robustand adaptive model predictive controllers are proposed for tracking a...
Adaptive robust control of fractional-order swarm systems in the presence of model uncertainties and external disturbances
, Article IET Control Theory and Applications ; Volume 12, Issue 7 , 2018 , Pages 961-969 ; 17518644 (ISSN) ; Tavazoei, M. S ; Sharif University of Technology
Institution of Engineering and Technology
2018
Abstract
This study investigates the asymptotic swarm stabilisation of fractional-order swarm systems in the presence of two different kinds of model uncertainties and external disturbances while the upper bound of the uncertainties is a linear function of pseudo-states norms with unknown coefficients. To this end, first a fractional-integral sliding manifold is constructed and then an adaptive-robust sliding mode controller is designed to guarantee the asymptotic swarm stability in a fractional-order linear time-invariant swarm system. The stability analysis of the proposed control system is done based on the Lyapunov stability theorem. Using the proposed controller, the coefficients of the upper...
Multiple model filters applied to wind model estimation for a fixed wing UAV
, Article Proceedings of 2016 7th International Conference on Mechanical and Aerospace Engineering, ICMAE 2016, 18 July 2016 through 20 July 2016 ; 2016 , Pages 109-115 ; 9781467388290 (ISBN) ; Nobahari, H ; Sharif University of Technology
Institute of Electrical and Electronics Engineers Inc
2016
Abstract
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...
Smooth residual generation for robust isolation of faults in manipulators using joint torque sensors
, Article 58th IEEE Conference on Decision and Control, CDC 2019, 11 December 2019 through 13 December 2019 ; Volume 2019-December , 2019 , Pages 2922-2927 ; 07431546 (ISSN); 9781728113982 (ISBN) ; Namvar, M ; Sharif University of Technology
Institute of Electrical and Electronics Engineers Inc
2019
Abstract
Reliability of model-based failure detection and isolation (FDI) methods depends on the amount of uncertainty in a system model. Recently, it has been shown that the use of joint torque sensing results in a simplified manipulator model that excludes hardly identifiable link dynamics and other nonlinearities. We present a geometric approach to fault detection and isolation (FDI) for robotic manipulators using joint torque sensor in presence of model uncertainty. A systematic procedure is introduced for representing a robotic system model using joint torque sensor being affine with respect to faults and disturbances. The proposed FDI filter has smooth dynamics with freely selectable functions...
A geometric approach to fault detection and isolation in robotic manipulators
, Article Proceedings of the IEEE Conference on Decision and Control, 17 December 2018 through 19 December 2018 ; Volume 2018-December , 2019 , Pages 391-396 ; 07431546 (ISSN); 9781538613955 (ISBN) ; Namvar, M ; Sharif University of Technology
Institute of Electrical and Electronics Engineers Inc
2019
Abstract
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...
Multivariable robust regulation of an industrial boiler-turbine with model uncertainties
, Article 9th International Conference on Modern Circuits and Systems Technologies, MOCAST 2020, 7 September 2020 through 9 September 2020 ; 2020 ; Moradi, H ; Vossoughi, G ; Sharif University of Technology
Institute of Electrical and Electronics Engineers Inc
2020
Abstract
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...
Sliding mode robust control of the horizontal wind turbines with model uncertainties
, Article 2020 9th International Conference on Modern Circuits and Systems Technologies, MOCAST 2020, 7 September 2020 through 9 September ; 2020 ; Moradi, H ; Vossoughi, G ; Sharif University of Technology
Institute of Electrical and Electronics Engineers Inc
2020
Abstract
Wind turbines are generally controlled based on two control objectives: Turbine protection and the generation of acceptable power for the grid. In this paper, a robust control strategy is presented for switching between various operating modes of the turbine. The rotor angular speed is hold below the allowable speed in all operation time. It is also attempted to catch a constant power in a desirable amount during the most of operation time. For the elimination of model/environmental uncertainties, sliding mode controllers are used. For the objective of power tracking, the stability of sliding mode controller is proved for a set of sliding surfaces. Advantages and disadvantages of the...
Iterative sparsification-projection: Fast and robust sparse signal approximation
, Article IEEE Transactions on Signal Processing ; Volume 64, Issue 21 , 2016 , Pages 5536-5548 ; 1053587X (ISSN) ; Babaie zadeh, M ; Sharif University of Technology
Institute of Electrical and Electronics Engineers Inc
Abstract
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...
A novel robust decentralized adaptive fuzzy control for swarm formation of multiagent systems
, Article IEEE Transactions on Industrial Electronics ; Volume 59, Issue 8 , 2012 , Pages 3124-3134 ; 02780046 (ISSN) ; Shabaninia, F ; Nemati, A ; Stan, S. D ; Sharif University of Technology
IEEE
2012
Abstract
In this paper, a novel decentralized adaptive control scheme for multiagent formation control is proposed based on an integration of artificial potential functions with robust control techniques. Fully actuated mobile agents with partially unknown models are considered, where an adaptive fuzzy logic system is used to approximate the unknown system dynamics. The robust performance criterion is used to attenuate the adaptive fuzzy approximation error and external disturbances to a prescribed level. The advantages of the proposed controller can be listed as robustness to input nonlinearity, external disturbances, and model uncertainties, and applicability on a large diversity of autonomous...
Comprehensive fuzzy multi-objective multi-product multi-site aggregate production planning decisions in a supply chain under uncertainty
, Article Applied Soft Computing Journal ; Volume 37 , 2015 , Pages 585-607 ; 15684946 (ISSN) ; Mahdavi, I ; Tavakkoli-Moghaddam, R ; Mahdavi Amiri, N ; Sharif University of Technology
Elsevier Ltd
2015
Abstract
The main focus of this paper is to develop a model considering some significant aspects of real-world supply chain production planning approved by industries. To do so, we consider a supply chain (SC) model, which contains multiple suppliers, multiple manufactures and multiple customers. This model is formulated as a fuzzy multi objective mixed-integer nonlinear programming (FMOMINLP) to address a comprehensive multi-site, multi-period and multi-product aggregate production planning (APP) problem under uncertainty. Four conflicting objectives are considered in the presented model simultaneously, which are (i) to minimize the total cost of the SC (production costs, workforce wage,...
Nonlinear robust adaptive sliding mode control of influenza epidemic in the presence of uncertainty
, Article Journal of Process Control ; Volume 56 , 2017 , Pages 48-57 ; 09591524 (ISSN) ; Moradi, H ; Sharif University of Technology
Elsevier Ltd
2017
Abstract
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...
A hybrid storage-wind virtual power plant (VPP) participation in the electricity markets: A self-scheduling optimization considering price, renewable generation, and electric vehicles uncertainties
, Article Journal of Energy Storage ; Volume 25 , 2019 ; 2352152X (ISSN) ; Ehsan, M ; Mousavizadeh, M ; Sharif University of Technology
Elsevier Ltd
2019
Abstract
The fast growth of technologies most of which depend on natural sources of energy has resulted in a huge consumption of fossil fuels. In this regard, many solutions have been suggested to alleviate the side effects such as air pollution and global warming. Among these solutions, mobile storages like electric vehicles (EVs) and renewable generations, have grown significantly due to being more applicable. But uncoordinated operation and uncertain nature of these distributed energy resources (DERs) can bring forward new challenges and issues to the operators of power system. Thus, in many cases it is more efficient to co-operate them in a hybrid system. In this study, we address a virtual power...