Sharif Digital Repository

In this research work, to enhance the performance of the conventional spinning disk reactors, a novel type of spinning disk reactor has been proposed and tested successfully through the synthesis of barium sulfate nanoparticles by means of the reactive precipitation. This reactor consists of two coaxial rotating disks placed horizontally in a cylindrical chamber. The experimental results clearly indicate the capability of the proposed reactor in the synthesis of nanoparticles with the smaller mean particle size and the narrower particle size distribution compared to those obtained in various process intensification devices such that barium sulfate nanoparticles with a mean particle size of... 

Due to the high cost and destructive effects of fossil fuels, the biogas production as a renewable and environmentally friendly fuel attracted much attention. In this regard, several targets are considered in this research. First, in order to increase of biogas production yield and accelerating the rate limiting steps in anaerobic digestion of wheat straw (lignocellulosic feedstock), the effect of additives containing trace elements (Fe and Ni) in form of nanoparticles and their salts was investigated through batch experiments. The results showed that addition of nanoparticles or salts resulted in the increase of methane production rate during the first 4 days of experiments. Then, a... 

In this work, nanoparticle production via microemulsion method has been investigated from theoretical and experimental points of view. Population balance approach has been used to model nanoparticle formation in an inverse microemulsion system. The study of nanoparticle formation in the inverse microemulsion system of Marlipal O13/40-cyclohexane-water reveals that in low reactants concentrations, the coagulation phenomenon has an important effect on the formation of particles. In this regard, the population balance equations has been developed to consider the coagulation phenomenon in the inverse microemulsion system. The kernel of coagulation has been calculated based on attractive and... 

In this work, a comprehensive dynamic model has been used for styrene emulsion polymerization in a semi-batch reactor to predict the evolution of product particle size and molecular weight distributions under non-isothermal condition. Method of moments has been applied for solving the population balance equations and the results are compared with the results obtained from finite-volume method as a precise technique. A sensitivity analysis respect to perturbation in initial values of various reagents, species and the reactor temperature has been performed to identify suitable manipulated variables for closed-loop control of the reactor. The detailed model is used to generate optimal feed... 

In this research work, mixed convection heat transfer of ferrofluids (i.e., magnetite nanoparticle) in a circular pipe fully filled with a porous medium in the presence of constant and alternating magnetic fields has been investigated both numerically and experimentally. The duct was heated by a heating coil and the magnetic field was applied via four electromagnets with U shaped ferrite cores and a frequency inverter. The nanoparticles were synthesized using co-precipitation method and coated with a surfactant (i.e., Tween 80) and doubled distilled water was used as the base fluid. To characterize the synthesized nanoparticles, various analyzing techniques such as VSM, SEM, and XRD were... 

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... 

Most of dynamical models in the real world, have various restrictions and complexities in their structures. These constraints make the controller design much more difficult. In this work, it has been tried to design the controller for two kinds of common dynamical systems in the presence of these restriction by using the fuzzy logic systems. Several restrictions are investigated in this project such as unknown dynamic of the model, unmeasured state variables, unknown control directions, existence of time delay in the input and the state variables, input saturation and controller singularity.The backstepping technique and the dynamic surfaces control approach have been used to design the... 

In this project design of adaptive neural network controller for uncertain nonlinear systems in the presence of different restrictions has been investigated. After providing introduction and motivation, two general forms of nonlinear systems including strict- feedback and pure- feedback have been introduced. In order to solve the problem caused by each restriction, a solution has been proposed. For the strict- feedback nonlinear systems several restrictions are considered such as, unknown dynamic model, unmeasured state, input saturation, unknown control directions, time delays in states and input. Stability analysis based on the Lyapunov theorem has been established. In addition, two kinds... 

In every year malaria has enormous fatality around the world, so this disease has to be controlled. In this thesis based on a model given in the literature[12], a model predictive controller has been designed and its performance has been compared with that of the optimal control. The simulation results show that in the case of model mismatch, the performance of model predictive control is superior. In model selection, it has been tried that a comprehensive model that has enough inputs for control to be selected. A linear time varying model is used to simulate the nonlinear behavior of the nonlinear system. The Least Squares method is used to update the model parameters  

Due to the importance of hepatitis disease, especially hepatitis C, from public health view point, this research aims to investigate and suggest an efficient medical therapy for this disease. First, available models are analyzed and the suitable one is chosen. Three controllers namely, fixed PI, adaptive PI and exact linearization control (GLC) are designed to control the hepatitis C disease using the drug efficacy as the manipulated variabel. Controller parameters are determined by the Genetic Algorithm (GA) and their performances are evaluated using the selected model. Uncertainties have been considerd in both model structure and parameters and controllers performances are investigated in... 

The purpose of this study is to propose a stable treatment strategy for hepatitis C infection by considering several practical limitations of the treatment and using control theories. First, hepatitis C disease and its transmission, diagnosis, and treatment methods have been introduced. Then, the mathematical models of hepatitis C dynamics in the body have been presented, and their ability in predicting the observed clinical behaviors of the patients has been studied. Thereafter, the extended versions of these models by considering pharmacokinetics/dynamics equations of the drugs have been proposed to have a more realistic mathematical model. After that, the practical features of the disease... 

Immediate control of pandemic influenza to avoid casualties and financial losses is an important issue. In this thesis, two types of controllers including optimal controller and adaptive generalized predictive controller based on linear input-output model, with vaccine, treatment and quarantine being controlling variables, have been used to control influenza. Each controlling methods were investigated for different states including single-input single-output and multi-input single-output. Single-input single-output and multi-input single-output models are identified as online and offline using least squares method. Since it is difficult to exactly identify the model parameters, especially at...