Sharif Digital Repository

In control systems, actuators are subjected to faults during operation. In the present work, a controller for nonlinear systems under several restrictions and in the presence of actuator failure has been proposed. The controller is designed for large-scale multi-input multi-output (MIMO) uncertain nonlinear systems subject to unmodeled dynamics, unknown state dependent control gain functions, unknown state time varying delay, unknown subsystems interactions, unknown external disturbances and input nonlinearity. The backlash has been assumed for input nonlinearity. No restriction has been considered regarding the number of actuator failure. The backstepping technique has been applied for... 

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 diesel fuel produced from vegetable oils or animal fats is called biodoesel. Biodiesel has desired fuel property as an alternative for diesel engines. Moreover, It is biodegerable, non-toxic, environmental friendly and has lesser undesirable exhaust. Due to biodiesel advantages, production of biodiesel and control of the biodiesel production reactor is noteworthy. The objective of this work is to control the mass fraction of the produced ester and the reactor temperature by manipulating methanol feed flow rate and the heat duty of the reactor. For this purpose, an adaptive multivariable generalized model predictive control (GPC) has been applied to the reactor. The results indicate that... 

The purpose of this thesis is design of an adaptive tracking control for input-quantized strict-feedback fractional order nonlinear systems with unknown dynamics and asymmetric time-varying output constraints. The controller design is achieved by using a hysteretic quantizer to avoid chattering and not needing the quantization parameters. The fuzzy logic method has been used to solve the problem of unknown dynamics. Also, due to the asymmetric time-varying output constraints, the Barrier Lyapunov function has been used. In this thesis, less restrictive assumptions have been considered than the work performed in previous researches.By utilizing the adaptive backstepping approach and based on... 

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... 

Switched systems as a subset of hybrid systems have both discrete and continuous behaviors and have attracted a lot of attention during the past decades. A set of subsystems or modes whose sequence is specified by a switching rule makes the switched system. Another category of systems is the fractional order system in which the order of derivatives is not limited to integers. This feature has provided a significant capacity for this type of system. On the other hand, every real system faces a set of limitations that neglecting them may reduce the quality of control or even lead to system instability. The purpose of this research is to model and control the switched system, whose subsystems... 

This work addresses adaptive neural control for a class of stochastic nonlinear systems in the nonstrict-feedback form. By introducing a nonlinear mapping, the output-constrained stochastic system transformed into a new system without constraint. The systems under study is subject to state time delay, input nonlinearity, unavailable states, unknown dynamics and actuator failure. The appropriate Lyapunov-Krasovskii functionals is used to compensate the time-delay effects, the neural network is used to approximate the unknown nonlinearities, the linear state observer is constructed to estimate the unmeasured states, and a variable separation method is used to deal with the difficulty caused by... 

The main objective of this study is evaluation of several nonlinear observers and comparing their performances.First, the literature review is presented; and then the process model is described. Second, observability and the observer design is disscused. Performances of Lunberger, sliding, and high gain nonlinear observers have been compared. Finally, the performance of a high gain observer in a closed-loop system including the back stepping controller has been evaluated.
 

Existence of time delay and interactions of control loops make control of multivariable delayed systems more difficult، therefore control of these systems is important. In this project a control scheme based on prediction of process output has been proposed. Traditional PI controllers are used in the control structure and controller parameters are tuned by genetic algorithm. Unlike the Smith predictor based methods، which become internally unstable when applied to unstable plants، unstable delayed multivariable systems can be handled by proposed method. It can also be applied to stochastic systems. The robust version of the control scheme has also been designed. Effectiveness of the proposed... 

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... 

In this thesis, a bioreactor with oscillatory and chaotic behavior has been studied and a control method has been proposed. This bioreactor shows oscillations for some special values of its parameters. The system dynamic is chaotic when a forced perturbation on the feed concentration is imposed. Dynamic behavior of this oscillatory and chaotic reactor has been illustrated. The main objective is control of product concentration. To do this, first system control is considered by proposing several control strategies for SISO case, then system in MIMO case is studied for achieving a globally controllable system. In SISO case, the performances of controllers are compared based on an objective... 

Methanol to Olefin (MTO) process is a part of the Methanol to Gasoline (MTG) production in a catalytic bed. Usually for this process, HZSM-5 or SAPO-n catalyst is used. In this research, dynamic modeling and simulation of the methanol to olefin catalytic reactor using HZSM-5 as the catalyst is done. The system is modeled based on the kinetic model for HZSM-5 presented by Castilla in 1999 [22]. Since the reaction is exothermic, taking use of a cooling system is essential. According to the high reactor temperature, a molten salt environment is used as the cooling media. In this cooling system, the molten salt absorbs heat of reaction from the reactor tubes and transfers it to a coil connected... 

Sudden pressure drop and then the gas shortage in city gas stations is one of the most important problems in high-pressure natural gas transmission networks. On the other hand, power consumption of compressors imposes a lot of cost on compressor stations. The conventional schemes to navigate the compressor stations are traditional methods based on experiment and trial and error which cause energy waste and violation of the optimal operating conditions. In this research, two manners of centralized- and decentralized- control are employed in order to navigate compressor stations in specified operating conditions regarding the operational and practical constraints. In this purpose, a sample gas... 

Polyethylene terephthalate (PET) is known as the most important polyester in the world. This polymer is the raw material for synthetic fibers, films and plastic objects and widely used in textiles and food industry. In this project transesterification and polycondensation reactors of a semi-batch process with dimethyl terephthalate/ethylene glycol feedare simulated. First simulations areperformed for reactors in the laboratory scale.Then the reactors are scaled up to industrial scale in order to produce 100 tons per year of PET product. The optimal temperature trajectory for the fisrt reactor is obtained based on a performance index. This performance index includes the reaction time and... 

This project presents appropriate strategies for HIV infection treatment. In order to close the presented strategy to real treatment regimen, appropriate parameters are selected for the HIV infection model, real outputs are considered for the system, and three widely used drugs (one PI: ritonavir (RDV), two RTIs: lamivudine (3TC) and zidovudine (ZDV)) are used to design a drug regimen. A Luenberger-like nonlinear observer (LNO) is also designed for estimation of unmeasurable states. In order to minimize the side effects of drug regimen, the concentration of ZDV is fixed at a minimum value at all time because this drug has a greater side effects than other drugs and the parameters of... 

Control of fermentation bioreactors with nonlinear behavior is a very important issue, especially when optimizing the biomass production is desired. The system in this situation works in two domains: minimum phase and non-minimum phase; and in transition from one domain into the other one the sign of process gain changes. For control of such a process in this work have been used two non-adaptive strategies and one adaptive strategy. The non-adaptive schemes are pole-placement and model predictive. The pole-placement technique as a linear control algorithm is used and its parameters are fixed by minimizing the objective function which has been used in predictive control technique. Another... 

The objective of this research is to design an adaptive controller for a class of fractional-order nonlinear systems in the strict-feedback form with unmodeled dynamics. Actuator saturation and actuator fault are also considered. All of the system states are assumed to be measurable, and all the sensors can be faulty. Fractional-order systems are chosen because, in the modeling of physical systems, the fractional-order calculus is often preferable to the classical integer-order calculus. The controller is designed by using the backstepping design technique. The fuzzy logic systems are used to eliminate the problem of "explosion of complexity" in the conventional backstepping method and also... 

Considering input constraints is an essential task in the controller design. In this thesis, a controller has been designed for incommensurate fractional order nonlinear systems in the nonstrict feedback form subject to unknown dynamics, input nonlinearity and actuator failures. The Lyapunov direct method and the backstepping technique have been used to design the controller and stability analysis. The number of actuator faults can be infinite. In addition, the proposed control algorithm can cope with different types of input nonlinearities namely, saturation, dead zone, dead zone-saturation, backlash and hysteresis. To estimate the system uncertainties, neural networks have been employed... 

The objective of this research is designing a controller for the event-triggered control of multi-agent systems in the presence of common constraints. In this regard, an adaptive decentralized event-driven controller is designed for the agents of a multi-agent system. The dynamics of the agents are nonlinear and unknown and they are subject to external disturbances. This controller is capable of achieving the objective of consensus with the desired performance in the presence of sensor and actuator faults, input nonlinearity, input and output quantization, and unmeasured states. The stability of the closed-loop system has been established via Lyapuonov theory. The considered multi-agent... 

In this research, it was tried to present a suitable environment for simulation of crystallization systems. Chapter one presented a survey on crystallization systems, its application, operating methods, and its phenomena. Chapter two presented mechanism and kinetic of phenomena that occur in crystallization systems, in detail, and mathematical models to modeling this systems are implied. In chapter three, that is the simulation result section, firstly, it focused on solution methods to solve population balance equation, that explains the particle size distribution, and its validation, secondly, the simulation results in a case study was compared with those obtained from finite volume method....