Sharif Digital Repository

Optimization always has been a major industrial field of study. Optimization is the process of finding the best result based on some events. In design, construction and maintenance of any kind of engineering system ,engineers must take a lot of decisions in the case of management or engineering at different levels in order to minimize the attempts to reach the optimum conditions and obtain the maximum profit on the other side. high speed of processing and litle time for calculations by using computers is very common nowadays which is caused in many improvements in optimization approaches. In this thesis some different classical optimization methods have been applied on Williams-Otto reactor... 

Artificial immune systems (AIS) constitute a novel area of bio-inspired computing. Biological models of the natural immune system, in particular the theories of clonal selection, immune networks and negative selection, have provided the inspiration for AIS algorithms. Moreover, such algorithms have been successfully employed in a wide variety of different areas, but have not been applied for chemical processes yet. One important part of the immune systems is lymphatic system. Clonal selection is one of the few algorithms that belong to the family of AIS techniques. Clonal selection algorithm is the computational implementation of the clonal selection principle. In this project, we have... 

In batch cooling crystallization, the crucial control problem is to design a temperature trajectory which produces a desired crystal size distribution. Here, a completely different solution is presented. Designing model-based controller for crystallizer has two steps; first step is determining optimal temperature trajectory which is some kind of feedforward control, second step is adding feedback controller (with manipulated variable of jacket temperature or cooling flow) to track the set-point (determined in first step) and rejecting possible disturbances. Traditionally, determining optimal temperature of crystallizer is done by using calculus of variations of distributed system. In this... 

In this thesis, a reduced model of a distributed one-dimensional Solid Oxide Fuel Cell (SOFC) system is presented. Consequently the reduced model is used to estimate the states of the exact model. The reduced model is derived using the exact solution of the distributed model and implementing the Karhunen-Loève-Galerkin procedure. To achieve an exact solution of the distributed model, method of lines is used. In the method of lines, accuracy of the solution depends on the number of grid points. To increase the accuracy, the number of grid points should be increased which will lead to a high order dynamic model. Such a model is not suitable for state estimation, optimization or control... 

There is many Nonlinear process in industry which are not control able with classic control methods. Model predictive control is a very useful method of control for nonlinear processes.
The nonlinearity of polymerization reactors are considerable in modeling, simulation, dynamic study and control .Design of free radical polymerization in continues reactors are very populated in industries.in this thesis modeling of free radical polymerization for polyvinyl acetate in industrial scale is studied for dynamic behavior studies of CSTR and design of Model predictive control system for the CSTR.
One of the important challenges in control system for this reactor is the existence of delay... 

this is one of the most widely used is the weighted residual method. The advantages of this method is likely to reach an appropriate solution is (in this project collocation method for solving systems of differential equations is used). After solving steady-state model with the lowest number of variables come to turn the control measures, including non-linear design of a Kalman Filter incentives that could be the orthogonal modulation system (which requires less computational time and good accuracy) as a representative of the system in the state estimation, optimization and control system used. In the end, offering a range of control methods such as multivariate linear and nonlinear... 

Selecting an appropriate control structure is an important subject in the design of control systems. Distillation column is one of the most popular and widely used unit operations in industry which complete understanding of its operability and controllability is one of the most important issues in the process control engineering. The present work studies the method of Output Controllability Index for nonlinear systems and compares it with Relative Gain Array and Condition Number. By using this index, the extent of intrinsic controllability of a process can be identified quantitatively in the absence of any controller. Also, the controllability of the process can be stated numerically or... 

Recently experiences in chemical processes approved that periodic operation for some of the processes (e.g. ion exchangers, activated sludge tanks, etc) were being successful. The performance and/or effectiveness of process due to periodic changes in the systems input, such as concentration, feed or coolant temperature and other possibilities, typically express whether in term of yield or selectivity improvement. Though, prominent issue in this type of dynamical control problem is optimal frequency and amplitude in the cycle. Supporting mathematics, include two main approaches: (1) the Hamilton-Jacobi approach based on the maximum principle and (2) a frequency domain approach using second... 

In this work, a model was presented for an MCFC fuel cell with internal reforming and combustion chamber. The model consists of mass and heat transfer equations beside the chemical and electrochemical reaction rate equations. Velocity distribution due to reactions and temperature distribution along the cell is considered. The model has been simulated in steady state form using finite difference method in MATLAB package environment accompanied by the analysis of the dynamic behavior of cell using method of lines in Simulink environment. Simulation results have been validated with experimental data extracted from literature. The last part of the work concerns with sensitivity analysis of some... 

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... 

In recent years, fuel cells have been proposed as an alternative option to conventional energy conversion systems. Fuel cell is an electrochemical system that can convert chemical energy to electrical energy without combustion. High efficiency, low temperature performance, poor pollution, good reliability, flexibility in the production potential, low start-up time and high life expectancy are the major advantages of this system. The most important barriers to the use of fuel cells are high cost polymer membrane and using expensive platinum catalysts. Modeling of fuel cells in general will meet two objectives. The first, due to the complexity of the processes taking place within the cell,... 

High efficiency and low-emission fuel cells have the capacity to replace fossil fuels for energy supply concerns. Solid oxide fuel cells operate in relatively high temperature and have power plant applications. Hence, they are acquainted to be coupled with cycle gas turbine to reduce the cost and increase the overall system efficiency. The control of these hybrid systems is so important. Due to the system nonlinearity and having more than one controlled variable, its control with classic methods would be difficult. The model based predictive control is used as an alternative to mitigate these difficulties. In addition to their high performance, their extension to the multivariate case would... 

In recent years, due to the development of smart wells, optimization of waterflooding by injection/production rate control has receivedsome interests. We can postpone breakthrough time and increase the sweep efficiency by using inflow control valves (ICV). Due to complexity of reservoirs, existence of constraints and numerous influencing parameters, we need a robust and suitable optimization approach to overcome such problems. In this thesis, model predictive control (MPC) is chosen to be our optimization approach. MPC is suitable for constrained multi variable functions. Genetic algorithm is was chosenas optimizer. Eclipse reservoir simulator was used for reservoir simulation. Eclipse input... 

Continuous synthesis of different kinds of industrial copolymers plays an important role in economics of the polymer industry. But copolymerization reactions are complex and with a high degree of nonlinearity so the control problem in this case needs a detailed study on system dynamic behavior. One of the solutions is using a optimal control method in the shape of predictive controllers. The main goal in this thesis is to design a generalized multi-varriable predictive controller for a solution copolymerization of methyl methacrylate and vinyl acetate in a continuous stirred tank reactor with separator and recycle stream. In this study, after simulating the nonlinear model of the process... 

High efficiency and low-emission fuel cells have the capacity to replace fossil fuels for energy supply concerns. Solid oxide fuel cells operate in relatively high temperature and have power plant applications. Hence, they are acquainted to be coupled with cycle gas turbine to reduce the cost and increase the overall system efficiency. The control of these hybrid systems is so important. Due to the system nonlinearity and having more than one controlled variable, its control with classic methods would be difficult. The model based predictive control is used as an alternative to mitigate these difficulties. In addition to their high performance, their extension to the multivariate case would... 

In this project, we have assessed the electrochemical treatment method. In this method, pH decrease of the place where a tumor is located engenders the necrosis of cancer cells and consequently they are destroyed. The process of pH decrease is caused by exerting voltage on electrods that are located near the tumor. The aims of optimizing this methods are to minimize the pH that results in the increase of cancer cell annihilation and to minimize the HClO and Cl2 products which are toxic and chage the healthy tissues to cancer cells. In this project, the model of electrochemical treatment method is explained, and then this model is simulated using the parametes which are provided in the... 

Today, shipping of liquefied natural gas has a considerable share in the global gas trade. Efficient design, optimal operation, and precise control of process variables in the gas liquefaction process decrease energy consumption for LNG production. Understanding the dynamic behavior of a liquefied natural gas unit helps engineers to make the correct choice of controlled variables and tuning controllers. Through a dynamic simulation, this understanding can be achieved. Simulation of a multi-stream heat exchanger, as the heart of the gas liquefaction process, is a challenge of studying this process. In this study, two dynamic models governing a multi-stream heat exchanger in Aspen Plus... 

Today, considering the global demand for reducing greenhouse gas emissions, rechargeable batteries are considered as a source of energy in electric vehicles, hybrid electric vehicles and smart grids. In all these applications for secondary batteries, the battery management system requires an accurate estimate state of charge of each cell. However, this estimate is difficult particularly for battery aging. In this study, a lithium-ion battery is modeled by using multidimensional multiphysics modeling and simulated in a comsol. In this simulation, the effect of the thermal conductivity coefficient on the battery temperature, initial salt concentration in electrolyte and the rate of discharge... 

Statistics show that cancer is the second leading cause of death in the world. In recent years, several studies have shown that combination therapy is more effective than single therapy. Modeling and simulation the dynamics of cancer and the immune system and controlling the dose of cancer drugs complement preclinical trials. The aim of this study was to apply the model predictive control approach to determine the optimal dose of chemotherapy and immunotherapy drugs to treat cancerous tumors. Thus, with a preliminary analysis of the analytics, a six-state dynamic model has been selected as a hypothetical patient to advance therapeutic goals. Two sets of parameters for the hypothetical... 

Dynamic modeling and control of bioprocesses, especially bioreactor and fermenter equipment, has always faced many challenges due to their complexity and high uncertainty. One scientific approach to modelling of such complex systems is the use of neural networks. Recently, an approach called hybrid networks has become popular, whose structure incorporates some of the basic rules, such as the mass balance of reactive species. Practically, it can also be used as a ‘software sensor’ or non-measurable state estimator. In this project, a bread yeast production bioreactor is used as a reference process and a hybrid neural network is used to estimate unknown parameters of biochemical reactions. In...