Sharif Digital Repository

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... 

Three different feedback linearization control methods are applied to nonlinear control of type I diabetes mellitus model. One is exact FBL and the two others are approximate manners based on approximations of the nonlinear system and its duality one-form, utilizing uniform approximation and a homotopy operator, respectively. An extended luenberger observer is also employed to observe the required states of designed compensators. The nonlinear compensators are designed based on a minimal model and applied to the minimal model, as well as Sorensen’s physiological model. In addition to the mentioned close-loop control strategies, a discrete control strategy based on an optimization problem is... 

Hybrid systems are the systems that in addition to their dependency on time, the occurrence of variouis events paly a vital role in their dynamic behavior. These systems inherit the characteristics of two inherently different categories of the dynamic systems which are: a) the continuous-variable dynamic systems; and b) discrete-event systems. Many systems in science and engineering can be considered as hybrid systems; among these one can mention the dynamic operation of stage wise processes, in which each mode of operation has its own dynamic behavior. Transition from one mode to another one is caused by the occurrence of various events. The main objective of this work is to investigate... 

Total Energy consumed in the compressor stations severely affects the gas transmission costs. Currently steady-state optimizations are used to solve “Minimize Fuel Cost Problem” (MFCP) in gas transmission networks. But due to the fast changing demand and maintaining the linepack of network, these methods are not able to find best solution for MFCP. Control of natural gas transmission system is a challenging task due to the system large dimension, lots of operating constraints and small number of measurements compared to the number of system states. In this thesis it is first shown that most of the pipeline systems have a mild nonlinear behavior. A heuristic method for identification of large... 

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... 

Natural Gas is one of the most important energy resources in the world. The U.S energy information administration(EIA) has reported that natural gas consumption will increase until 2030 in all participating sectors including industrial, domestic and electricity production.Although the use of natural gas as a source of energy has many advantages, natural gas physical condition made it’s transfer so challenging. Among the various types of transmission methods, using pipline is so conventional. Natural gas can be transmited through pipelines in a safe and reliable manner upto thousands of kilometers. For this reason, operation monitoring and control of gas transmission networks are so... 

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... 

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... 

An anatomically accurate model of conducting airways is essential for adequately simulating gas mixing and fluid distribution. In the current study, Lindenmayer systems (L-systems) as a type of graph grammars method has been formulated to generate bronchial tree structure in human lung. It has been considered that the structure of bronchial tree is divided into two main parts: 1) The central airways (from the trachea to segmental bronchi); and 2) the dichotomous branching structure (from segmental bronchi to alveolar duct). Nine parametric rewriting rules incorporating within physiological laws of the airway branching are used to generate each parts of the bronchial tree. Comparison of the... 

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... 

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... 

Simulation of biological behaviors as the pre requirement for control and optimization, especially for recognition and treating diseases, requires studying involved reactions which may or may not be accessible. In the other side, finding the correct network structures and related mathematical expressions to simulate biological behaviors is a complicated problem due to multi aspect interactions among biological reactions, which imply an approach that integrate the knowledge coming from multiple discipline including biological concepts, mathematical modelling, bioinformatics and advanced programming. In this study we aim to analyze this problem using ontological inference to develop a... 

In this study, in order to enhance data contaminated with random and gross errors, the implementation of data reconciliation technique on large-scale industrial unit was investigated. Data reconciliation results on the naphtha reformer unit, revealed that uncertainty in estimation of input and output reactor temperatures, decreased up to 2% in comparison with measured ones. In addition, uncertainties in estimation of the mass flow rates have declined by nearly 30%. Also, an object-oriented framework for plant wide data reconciliation was designed. This framework was designed as an extension of plant wide identification software developed previously. Moreover, adding five classes to the... 

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... 

Access to a reduced and fast mathematical model that can predict the input-output behavior of interconnected systems with acceptable accuracy and in a short time is crucial. The purpose of this project is to provide an object-oriented platform for identifying a model based on input-output data of interconnected systems in real-time. On this basis, in the case of developing fast estimation algorithms and updating the model quickly (in case of extensive changes in the system), good predictions of the model can be used for various applications. In this research, machine learning and data analysis methods are used to extract useful features and relations from data. Then, taken advantage of this... 

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... 

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... 

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... 

Gas transmission networks play an important role in multi-vector energy networks. Therefore, reliable and efficient control of gas transmission networks with the minimum energy consumption is utmost task and is still an active research area. This work, introduces a distributed, model-free, and game-theoretic approach comprising a simultaneous game followed by a sequential game, to achieve the control objectives in gas transmission networks. The cooperative game approach is adopted for this purpose. In the proposed method two fuzzy inference systems have been used to obtain the payoff of each player in the game of gas transmission network control, the first one has been used to determine the... 

Gas transmission networks, as one of the most important energy transport networks, are used to transport gas from production facilities to major gas consumers. These networks possess very complex behavior due to their severely nonlinear equations, their temporal and spatial broadness, the compressibility feature of the fluid that passes through them, and their relationship and interdependency with other energy material generation, transportation, and distribution infrastructures through multi-vector energy systems. Hence, the management and coordination of these networks are challenging. In this regard, the most demanding problem of such networks is their expansion planning due to the...