Sharif Digital Repository

This study opens up new horizons in data-driven structural identification methods offering extensive improvements over the existing time-/frequency-domain probabilistic methods. It pushes forward a holistic Bayesian statistical framework to integrate the existing formulations under a hierarchical setting aiming to quantify both the identification precision and the ensemble variability prompted due to model errors. Since the computation of the posterior distributions in hierarchical models is expensive and cumbersome, novel marginalization strategies, asymptotic approximations, and maximum a posteriori estimations are proposed offering mathematical formulations for the uncertainty... 

DC-DC switching convertors are power electronic circuits that have various applications nowadays. Quasi-resonant convertors are a kind of these convertors that are of great interest due to their simple structure and soft switching. The goal of controlling these convertors is to achieve constant output voltage while varying the input voltage and the load by choosing a proper switching frequency. Classic controllers show drawbacks in the case of high input voltage and load tolerance, and this nonlinear behavior of the systems results in some practical challenges. In this thesis, nonlinear predictive controller for quasi-resonant Buck convertors is designed. Having designed the linear... 

n the present study, the optimal design of feeding system in steel sand-mold castings is considered. The first part of this research includes fundamental studies on the physics of shrinkage defect formation during the casting process. The results of these studies lead to new findings on the mechanism of shrinkage defect formation, effect of melt quality on the distribution of defects within the castings and the connection between shrinkage and gases defects. The theoretical analysis of thermal criterion functions for the prediction of shrinkage defects in castings and introducing new criterion function with fewer shortcomings can be accounted as the other finding of this part. A new model... 

In industries there are many nonlinear processes which cannot be easily controlled with classical methods. Model predictive control is a useful method for nonlinear processes which not only has high efficiency, but also extension of this control to interferential multi variable case, with constraint on the controlled and manipulated variables and other problematic dynamic specifications such as slow dynamics and inverse response is very simple. Industrial polymerization processes are regarded as significant nonlinear processes. Optimization and control of polymerization reactors have considerable importance in process applicability and in economics. The molecular structure of polymer such as... 

Epilepsy is one of the most significant neurological disorders that about one percent of people suffer from it. Epilepsy can only be controlled, and so far no cure for it has been provided. Despite the many advances in the treatment of diseases, for a quarter of patients there is no medical treatment solution for controlling epileptic seizures. In the studies of medical groups on the epilepsy, one approach is employment of some models for each type of epilepsy. These types may be created in the animals to allow studying of the mechanism of epilepsy and also finding drugs of treatment or controlling seizures for each type of epilepsy. There is a type of epilepsy that is called absence... 

Anesthesia control during surgeries has been greatly considered in recent years. In this thesis nonlinear and linear control algorithems are implemented to control the human anesthesia system. First, non-adaptive linear model predictive algorithem is tested. Since the model parameters change from one person to another, adaptive algorithms seem more suitable for the system. Therfore, adaptive linear predictive control is implemented in the next step, and it shows a better performance. According to the system nonlinearities, non-adaptive nonlinear model predictive control (NMPC) based on the state-space model is also applied to the system and it has a better performance index. The main problem... 

Studying data flows in conventional applications of Multi-Processor System-on-Chips (MPSoCs) denotes that most of these flows are the ones that transfer huge volume of data in inter-core communications. Previous works try to present architecture for interconnection network which some paths with low power and latency are reserved (statically or dynamically). However all of the presented methods are based on subnetworks or mechanism of transferring control messages (to establish a path and tear it down after transmission of data). Optical connections with low cost, low power and high bandwidth are good candidates to reduce power consumption of Network-on-Chips (NoCs). Therefore, using optical... 

The constrained nonlinear systems with large operating regions have attracted great attention due to their correspondence with the most practical systems. There are several tools such as gain scheduling and Nonlinear Model Predictive Control (NMPC) to control them. Gain scheduling, with ability to provide stability guarantees between the estimated stability regions overlapping each other and to cover a large space of the allowable operating range of the system, is an attractive practical approach to control the systems with large operating regions. But this strategy do not account for constraints explicitly by online optimization. On the contrary, NMPC handles constraints on the manipulated... 

The land market is one of the most important markets in the economy. Land is a factor of production, store of value, and a major part of household’s portfolio. Although price of land is an essential information for institutions like municipalities whom tax the landlords, or for financial intermediaries like banks whom use the land as collateral, studies about price of land and its spatial and time variations are scrace in Iran. Furthermore, most of studies in other countries are usually based on inflexible OLS estimators. Thus, this study has two main contributions. First, to analyze the usefulness of hedonic modeling in explaining the price of land, utilizing a unique dataset for Tehran... 

A group of vehicles are contributed to follow static or dynamic targets in a cooperative target tracking problem. The vehicles estimate the future location of dynamic targets based on the information they receive from other vehicles and targets. Noting to these estimations, the vehicles are able to decide the best movement toward the targets. Various control methods have been presented to solve different problems of target tracking which the majority of them proposed optimal control solutions. A new approach to the problem of tracking dynamic targets via cooperative multi-vehicle systems under the receding horizon control of the vehicles is proposed in this dissertation. A receding horizon... 

In the industry, there are nonlinear processes that can not be controlled with classical methods. Also, there are many processes that are more than one controlled variable that with classical methods, the design of a multiple input - multiple output controler is very difficult for them as well as the constraints on the inputs and outputs of the process exist, using classical controllers will be far more difficult. A model-based predictive control method for controlling nonlinear processes is useful in addition to having very high efficiency, extended to multi-mode interference together with constraints on the control variables and other controlled Problem with dynamic properties such as... 

Wireless sensor networks (WSNs) can be used in a variety of applications. The prime shortcoming of these networks is their energy constraint. The main energy consumer in a sensor node is its radio transmitter. Therefore data prediction is one of the most effective methods to reduce the data transmission rate. By data prediction, a large amount of energy is saved; which results in the longevity of the network life. Environmental variations almost have similar effects on different sensor sources in a sensor device. So, considering the correlation between different sources reduces the noise impact and increases data prediction accuracy. In this thesis, we use temporal and multisource... 

Due to the advances in wireless communications and electronics over the last few years, the development of networks of low-cost, low-power, and multifunctional sensors has received increasing attention. Most important constraints of this network are energy and bandwidth. Data aggregation is one of the effective approaches for reducing energy consumption in wireless sensor networks. Recent research on data collection reveals that, rather than reporting data through long, multi-hop and error-prone routes to a static sink using tree or cluster network structure, allowing and leveraging sink mobility is more promising for energy efficient data gathering. In this work we proposed an effective... 

Nowadays, some of the major problems of the airplane industry is that airplanes’ fleet are approaching to the end of their defined life, inability to buy new planes and obtaining aircraft’s parts for repairing process. Therefore, in order to increase the life of the aging aircrafts, some essential process such as modeling processes, identify principal structure elements to strengthen and repair them should be done to all these airplanes, all these processes refer as aging process. Aging programs initiated in some countries, such as America, Australia, Britain and Canada from about thirty-five years ago, technological approaches inventing new ways to start repairing worn metallic structures... 

By increasing speed gap between microprocessors and off-chip Last Level Cache, Optimization in Last Level Cache makes improvement in system performance. With development of new generation of multi-core processors and sharing LLC between these cores, the so called issue of Memory Wall has caused an incremental effect of LLC on system performance. There are three approaches to use this memory more efficiently:
1. Increasing cache capacity
2. Making cache hierarchical and adding different layers to hierarchy
3. Improvement of replacement algorithms in cache memory
The first approach has not been used in regard with limitation of technology and growth of access time due to... 

A distributed model predictive control with two-layer structure for communication is presented in the present thesis for elimination of the propagation and amplificationphenomenon of the upstream transient errors in automated irrigation networks. This phenomenon results in the saturation of actuators in long automated irrigation channels and therefore it results in significant reduction in the quality of service of the irrigation network. Hence, the elimination of this phenomenon in long irrigation channels is necessary, in which a distributed model predictive control with two-layer structure for communication is presented in the presentthesis for elimination of this phenomenon. Feasibility,... 

This thesis deals with identification of Errors-In-Variable(EIV) models with Compensated Prediction Error Method (CPEM). In EIV model structure, noise affects both on input and output data. We introduce a method to identify linear and discrete EIV models where the conventional PEM in classical identification, has been used in. Using PEM on EIV models leads to a biased estimation. Therefore, the reason of incorrect estimationobtained from PEM in the presence of input noise is investigated and the importance of consideringthe input noise is explained. Then by introducing two modifications, we try to compensate the deficiencies caused due to the presence of input noise. First, some changes are... 

Expert retrieval when the number of experts are limited is an open problem. Undoubtedly, becoming an expert in a field is a time consuming and expensive task; thus finding the best candidates is a crucial task. In addition, passage of time and growth of knowledge could change the view of a person towards life and his work, which may lead to the change of his or her field of work. When considering the changes each person makes in his or her life, it becomes obvious that they are not far from the original status. Therefore, recommending all possible options around a person could really help the task of decision making. This research is addressing two similar issues of finding experts, in a... 

One of the main causes of low back pain is mechanical loads acting on it. These loads can be measured by in vivo measurement using force and pressure sensors. Although this method leads to accurate results, it is invasive and costly. Currently the only noninvasive way to estimate these loads is to utilize biomechanical models. Using these models requires body posture as an input. Imaging techniques are suitable for determining the posture accurately, but these equipments are expensive and often impractical. So today posture prediction models are used as an alternative cost effective with acceptable accuracy. These mechanisms predict body posture using body mass, height, position and the... 

The purpose of this project is to study the interactions between process design and process control in a gas transmission pipeline. A part of gas pipeline in two conditions is considered, 1: The gas pipeline that has nominal structure and 2: the one with optimal structure by using an economic objective function that considers the capital and operation cost. To aim this object, by creation of an interface to communicate decision variables between MATLA (as an optimizer and controller engine) and Aspen HYSYS (as a pipeline simulator) is attempted to design and then control the pipeline with to control algorithms PI and MPC. Finally the interaction between process design and process is...