Sharif Digital Repository

Stabilizing unstable periodic orbits of a deterministic chaotic system which is perturbed by a stochastic process is studied in this paper. The stochastic chaos is modeled by exciting a deterministic chaotic system with a white noise obtained from derivative of a Wiener process which eventually generates an Ito differential equation. It is also assumed that the chaotic system being studied has some model uncertainties which are not random. The sliding mode controller with some modifications is used for stochastic chaos suppression. It is shown that the system states converge to the desired orbit in such a way that the error covariance converges to an arbitrarily small bound around zero. As... 

Although there are many works in which path planning of robots is studied, but path planning of the bevel-tip needles with highly flexible body is different and difficult due to unique properties of soft tissues. Real soft tissues are nonhomogeneously elastic and uncertainly deformable and hence, during needle motions the planned path changes unknowingly. In this paper, a novel adaptive path planning of bevel-tip needles inside the uncertain brain tissue is presented. The proposed approach is based on minimization of a Lyapanov energy function used as the cost function which consists of 6 partial costs: path length, number of changes in bevel direction, tissue deformation, horizontal and... 

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... 

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... 

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... 

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... 

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... 

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... 

Application of fractional order PID (FOPID) controller to an automatic voltage regulator (AVR) is presented and studied in this paper. An FOPID is a PID whose derivative and integral orders are fractional numbers rather than integers. Design stage of such a controller consists of determining five parameters. This paper employs particle swarm optimization (PSO) algorithm to carry out the aforementioned design procedure. PSO is an advanced search procedure that has proved to have very high efficiency. A novel cost function is defined to facilitate the control strategy over both the time-domain and the frequency-domain specifications. Comparisons are made with a PID controller and it is shown... 

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... 

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,... 

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... 

Purpose - The purpose of this paper is to present a novel approach in aeroservoelastic analysis and robust control of a wing section with two control surfaces in leading-edge and trailing-edge. The method demonstrates how the number of model uncertainties can affect the flutter margin. Design/methodology/approach - The proposed method effectively incorporates the structural model of a wing section with two degrees of freedom of pitch and plunge with two control surfaces on trailing and leading edges. A quasi-steady aerodynamics assumption is made for the aerodynamic modeling. Basically, perturbations are considered for the dynamic pressure models and uncertainty parameters are associated... 

Range of motion (ROM) of the thoracic spine has implications in patient discrimination for diagnostic purposes and in biomechanical models for predictions of spinal loads. Few previous studies have reported quite different thoracic ROMs. Total (T1-T12), lower (T5-T12) and upper (T1-T5) thoracic, lumbar (T12-S1), pelvis, and entire trunk (T1) ROMs were measured using an inertial tracking device as asymptomatic subjects flexed forward from their neutral upright position to full forward flexion. Correlations between body height and the ROMs were conducted. An effect of measurement errors of the trunk flexion (T1) on the model-predicted spinal loads was investigated. Mean of peak voluntary total... 

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...