Sharif Digital Repository

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... 

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... 

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... 

Persian Gulf is a semi-enclosed highly saline reverse estuary that is exposed to the risk of oil spills in offshore oil and gas activities. In the early 2000s, a specific version of NOAA's Trajectory Analysis Planner (TAP II) was developed for Persian Gulf to assist regional organizations in preparing oil spill contingency plans. In this research, a new stochastic model is developed to cover the limitations of TAP II. The new model is based on an advanced trajectory model, which is now linked with high resolution spatiotemporal data of the wind and sea current. In a case study, the developed model is compared with TAP II, and evaluated by multiple tests designed for analysis of uncertainty,... 

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... 

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... 

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... 

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 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... 

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... 

The present study aims to present a guidance algorithm based on the relative motion prediction for orbital rendezvous, in which a coast phase is allowed between two powered phases. In both powered phases, the solution of the Hill-Clohessy-Wiltshire equations is used to find the required state variables at each time instant. To track the required trajectory and compensate for any orbital perturbations and uncertainties, a non-singular terminal sliding mode method is utilized as the steering law. Then, the finite time convergence of the state variables is mathematically proved. In addition, the starting time of the second powered phase is adapted to perturbations and uncertainties by another... 

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.... 

In this paper, a new impedance-based teleoperation strategy is proposed for assist-as-needed tele-rehabilitation via a multi-DOF telerobotic system having patient–master and therapist–slave interactions. Unlike a regular teleoperation system and as the main contribution of this work to minimize the therapist's movements, the therapist's hand only follows the patient's deviation from the target trajectory. Also it provides a better perception of the patient's problems in motor control to the therapist The admissible deviation of the patient's limb from a reference target trajectory is governed by an impedance model responding to both patient's and therapist's interaction forces. As the other... 

This paper proposes a methodology for generating surrogate single-degree-of-freedom (SDOF) models that can be utilized to estimate the probability distribution of the roof drift ratio of multistory buildings at various ground motion intensity measures. The use of an SDOF model as a surrogate for multistory buildings can significantly alleviate the high computational cost for probabilistic seismic demand assessment considering both model uncertainty and record-to-record variability. The surrogate SDOF model generated herein explicitly accounts for model uncertainties and can be used as an alternative to the nonlinear dynamic analysis of detailed building structures. Applications for such... 

In this paper, an adaptive critic-based neurofuzzy controller is presented for water level regulation of nuclear steam generators. The problem has been of great concern for many years as the steam generator is a highly nonlinear system showing inverse response dynamics especially at low operating power levels. Fuzzy critic-based learning is a reinforcement learning method based on dynamic programming. The only information available for the critic agent is the system feedback which is interpreted as the last action the controller has performed in the previous state. The signal produced by the critic agent is used alongside the backpropagation of error algorithm to tune online conclusion parts... 

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... 

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... 

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... 

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...