Sharif Digital Repository

In this project a framework for Model Based Fault Diagnosis (MBFD) in a Gas Transmission Network (GTN) was developed. A black-box linear state-space model was used to capture dynamic behavior of an industrial benchmark for GTN. A full fledge commercial network simulator were used to obtain the required data for process identification. In order to check the robustness of the model zero mean white noise was imposed on various output obtained by the commercial simulator. Kalman filter was used to estimate the states of the GTN. These estimated states along with the measured output (all obtained from the commercial simulator) are almost similar to their corresponding estimated signal. This shows... 

In control engineering we want to set dynamic behavior of the system to a desired one and having a model that simulate systems behavior is necessary . System identification is a branch of chemical engineering that provide us this model , which divided into different branches itself . In this project we use object oriented programming to design and implement a software that support black box models such as Neural networks in addition to Mechanistic models (Which was implemented in previous project ) for identification . We use UML and C++ language in C++ Borland Builder in this project  

The main objective of Control Engineering is to lead dynamic behavior of system to an arbitrary state, accomplishment of such an objective requires a model which somehow represents the dynamic behavior of the system, On the other hand an accurate yet fast and efficient model of a complicated model cannot be easily obtained based on the original inputs, states and outputs of the system. This is true both for mechanistic (white box) and empirical (black box) models. In this project, the previous frame work developed for object oriented plant-wide identification has been extended to cover the model reduction based on various established procedures in this area (e.g., statistical and intelligent... 

A modeling framework is proposed for complex chemical process networks. Concept such as passivity systems, thermodynamic function and graph theory are some important and applicable concept which seems to be useful for process network. The state is represented by energy, volume and mass inventories. The dynamic behavior of the process system is constrained so that all trajectories satisfy the first and second laws of thermodynamics. The concavity of the entropy function is used to define a storage function for passivity design. The proposed storage function is closely related to the Gibbs tangent plane condition. Stability analysis, pairing and controller design could be done by this new... 

Whenever continuous and discrete dynamics interact, hybrid systems arise. Basically, models of such systems consisted of differential or difference equations to represent continuous dynamics and automata or other discrete variables to describe behavioral mode of the systems. Our main concern is focused on two types of hybrid systems: Discrete controllers which are combined with continuous physical process like biological systems can often be well described by hybrid systems. Our approach in this thesis deals with optimal multiple daily insulin injections which are introduced as an offline control approach on a simulated patient with type I diabetes. Simulated patient is provided via GlucoSim... 

A statistically-based method has been developed for automated identification of steady state. The method is computationally inexpensive when compared to conventional techniques. The R-statistic is dimensionless and independent of the measurement level. Because it is a ratio of estimated variances, it is also independent of the process variance. Simulations show that for recommended critical values are also effectively independent of the magnitude and distribution of the noise.
A fuzzy-logic-based methodology for on-line steady state and transient state identification is introduced. Although steady state identification is complicated by the presence of noise, fuzzy logic can help capture... 

The kidney is one of the most complicated organs in terms of structure and physiology, in part because it is highly vascularized. Previous investigations have focused on specific characteristics like length and diameter. There are a few methods like those which are based on image processing techniques, that have been focused on all features as a unique structure. The clear drawback of these approaches is inability to justify growth and changes. Lindenmayer system (L-system) is parallel rewriting method and a type of graph grammars. L-system can justify growth and all characteristic changes and adopt itself to them. Parametric rewriting rules incorporating within physiological laws of the... 

In this work, a non-isothermal model of natural gas in pipelines including mass, momentum and energy balance equations are used as model equations for modeling and state estimation in gas pipeline systems. An algorithm is proposed to handle the discontinuities that appear in the dynamic model of a GTN. The states of GTN are estimated using the continuous/discrete form of the extended Kalman filter for two benchmarks and some heuristic rules for sensor placement in a GTN are concluded. Also, a framework for distributed and decentralized state estimation in high-pressure and long-distance gas transmission networks (GTNs) is proposed. Some heuristic rules are suggested for system decomposition... 

In recent years, due to the energy price increase, great efforts were made to optimize the operating conditions of various chemical processes in order to reduce the operating cost and obtain the maximum possible profit. Decision makers should usually deal with different kinds of uncertainty in process optimization. In this situation, fuzzy optimization is an ideal method, since it represents and handles the underlying uncertainty of the optimization problems. In this paper, the optimization problem for production process of dimethyl ether (DME) as an alternative fuel to diesel is considered. Both crisp and fuzzy approaches are applied to formulate the optimization problem while sensitivity... 

Monitoring of natural gas transmission networks, is one of the necessities for efficient, safe, and economical operation of energy supply networks. In order to efficiently control and monitor the operation of gas transmission network, various states of the network (like temperature, pressure, and flow) should be available. Among these states, some can be easily measured, and the rest should be estimated based on these measurements throughout the network. In this project, an algorithm to obtain near optimal locations of various measuring devices has been proposed. Furthermore, a method for estimation of the states of transmission network based on these measurements and Machine Learning has... 

A mathematical model helps to understand any system with any level of complication, such as the human body. The heart, vascular system, and lungs are three important parts of each body that life is impossible without them. The performance of the cardiovascular and respiratory systems is tuned by a group of complex mechanisms which are called regulatory mechanisms. Therefore, a model which describes the behavior of these mechanisms has great importance. The goal of this research is to provide and simulate the newest and most complete model in this field. The presented model should consist of the heart, vascular system, lungs, respiratory system, gas exchange and transport, and finally... 

Multi-vector energy (MVE) networks are one of the most complex systems which are attractive to many researchers. In this work, an integrated gas-power transmission network as an MVE network has been studied. The MVE benchmark used in this work comprises a gas transmission network, which is the core of the MVE, a power transmission network, and a Syn-Gas plant. The gas transmission network supplies the gas demands of its consumers. The main objective of this thesis is to design appropriate controllers to maintain the states of the gas network in its desired condition. Since the gas network is distributed parameter system and its model is an infinite dimensional state space, it is either... 

Monitoring of the water transmission networks is an essential factor to regard efficient, safe and economical strategic considerations. Several parameters (fluid pressure, fluid flow and fluid temperature in some cases) are measured to monitor the water transmission networks. The number and location of these measurements in deferent positions affect the cost and quality of the network states monitoring. It is obvious that measuring the all parameters and states of the network is not cost-effective even when it is possible. The conventional sensor-location methods have been developed based on the pressure variation stemmed from a leakage in the network. This study proposes a new procedure to... 

Increasing demand for natural gas in various parts of energy sectors results in the rapid boost of analysis tools necessitates the development of the appropriate pieces of software for both simulation and optimization of the transient behavior of the gas transmission networks as an important part of the gas industries. The main objective of this project was the development of a dynamic and compositional simulator in an extensible, robust, reusable and yet maintainable manner. To achieve this goal, the object-oriented approach was used as the software development paradigm. After going through the analysis and design of this software based on an object-oriented methodology, it has been... 

The bronchial tree consists of two main parts: conducting airways and respiratory airways. Parametric Lindenmayer System (L-System) has been used for modeling of the structure. The conducting airways are divided into two parts: central region consisting of trachea up to segmental bronchi and bronchioles located in the bronchopulmonary segments. The boundary of these segments has been found by image processing techniques. Stochastic Parametric L-system has been used for modeling of acinar region. To find the characteristic properties of conducting airways and respiratory bronchioles, an intelligent method has been developed. The parameters of the model are either age dependent or... 

Fault diagnosis in complex processes is very difficult due to their complexity and dimensionality, so it is of great importance. In previous works, concurrent fault diagnosing methods have not been able to diagnose faults with overlapping symptoms. On the other hand, there is no established and general method by which asynchronous concurrent faults with overlapping symptoms can be diagnosed. The purpose of this work is to come up with such a method in order to mitigate the shortcomings of the available methods which are not appropriate to be used for such a problem. In this problem, the main objective is to come up with course of events of faults according to their times occurrence. The... 

In plant-wide systems, faults can easily propagate due to the interconnection of streams. The main objective of this paper is to develop a systematic framework for online decision support system (DSS) in order to make the right decision to get the process out of critical conditions (which cannot be handled by the plant controllers) smoothly. One of the key features of the proposed approach is its lack of dependence on prior knowledge of the fault signals (e.g. number of faults, and their origin). In the proposed scheme, the plant is modeled by a fuzzy directed graph (FDG). The proposed scheme utilizes a backward reasoning based on the deviations that exists in the process variables... 

Monitoring and control of gas transmission networks are very challenging and important, this is due to the fact that interactions between various elements in the transmission network severely affect network’s overall performance. This makes it crucial for the monitoring and control systems to take into account the topology of the network, in their decision making and control scenario’s. On the other hand, in the event of any abnormality in the network behavior, , in order to accurately and quickly detect the cause of the abnormal conditions, there is a need for rapid and effective analysis of the network based on the measurements made therein and to identify the key and effective situations... 

Identification and control of nonlinear systems have been always such important subjects based on nonlinearities of many processes. For instance, identification and control of gas transmission networks can be mentioned as one of the challenging problems related to their complexity and existence of different variables. The purpose of this project is identification of a nonlinear model for defining a gas transmission network and implementing a model predictive control algorithm based on identified model. Hence, first, a volterra model is implemented for identification of a pH neutralization process and then, that model is used for identification of a gas transmission network. Finally, by... 

Fischer-Tropsch (FT) is a process which is studied recently by many companies and researchers. Due to limited sources of petroleum, conversion of Synthesis gas to liquid hydrocarbons as gasoil, gasoline has been considered a lot from 1980. In this thesis new design for FT process is presented (based on Fe-Cu-K catalyst) to produce gasoline, gasoil and wax, this design is simulated by HYSYS 3.1 software. Lumping strategy of reactions involved in FT mechanism is used to reduce simulation time. Not being FT reactions in HYSYS, reaction extensions are used (via customization capability) to include complex lumped reaction rates. Afterward, PI controller is implemented to control concentration...