Sharif Digital Repository

Controlling the nonlinear processes is very important in industry. In this thesis, model predictive control is considered as a nonlinear control strategy and two nonlinear models, namely wiener and Hammerstein models are used and their identification methods are described. State-space model is also considered and closed-loop stability has been studied. Another strategy for controlling the nonlinear process is global linearization control. Some concepts and related theorems for this strategy are stated. PID controller is used as a linear controller for this strategy. In this model for estimating the state and load, two nonlinear observers are used. Stability analysis of output feedback... 

The object of this research is modeling, simulation and control of a crystallization process. Population balance equation (PBE) has been used for modeling of such processes. Most of the existing numerical methods cannot solve the general form of PBE in presence of the breakage and agglomeration terms and some others are not suitable for control objectives, because of their intractable CPU time. In this work a new developed numerical method called conservation element and solution element (CE/SE) has been used for solving general form of multidimensional population balance equations. The accuracy and effectiveness of the scheme is demonstrated through computer simulation. According to the... 

Chaotic behavior takes place in different physical systems such as chemical reactors. In this thesis, dynamical behavior of chemical reactors in which polymerization or series reactions take place has been considered. It has been shown that these reactors have chaotic dynamics under special condition. Two reactors of the second type (with series reactions) for cases of known and unknown parameters have been synchronized by a control method and stability of the proposed scheme has been established by the Lyapunov stability theorem. Simulation results show the effectiveness of proposed method. Since concentration measurement is difficult and expensive, an observer has been used for... 

This thesis concerns the modeling of precipitation processes aimed at predicting product particle characteristics especially particle size distribution. A mixing-precipitation model (based on SFM) linked to the population balance is used for a single-feed semi-batch precipitation process to describe the mixing effects on the final particle-size distribution (PSD) and mean size, considering the agglomeration mechanism. The model describes mixing on two zones: the feed and bulk zone with different levels of super saturation. To solve a full population balance equation containing nucleation, growth and agglomeration, discretization method was performed witch is more accurate and low... 

This research is trying to investigate the control algorithms of unknown control direction systems. Since Nussbaum function is the most common method which in used for these systems this research focus on this algorithm to overcome control the effect of unknown control direction. This research study the performance of different control algorithms in controlling such systems followed by analysis of two control modes of continuous and discrete using Nussbam Function. Additionally, in continuous mode, the performance of two methods of backstepping and liding mode has been compared on the given system in variety of situation. Results demonstrate that backstepping method shows better performance... 

In this study, adaptive control of HIV infection was investigated based on feedback linearization. First, three state model of HIV infection was simplified to implement the adaptive approaches by using some assumptions. Then, adaptive control method based on feedback linearization was implemented on reduced order and three states infection dynamic model with including the RTIs and PIs drugs effects as control input. The parameter projection method, adaptive nonlinear observer and dynamic anti-windup were employed in implementation of adaptive control method to prevent singularity problem, to estimate system states and to avoid windup problem of external PID controller, respectively. Finally,... 

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... 

Final control elements usually have nonlinear dynamics which affect the stability of the closed- loop system. Four most common types of these nonlinearities are dead-zone, backlash, hysteresis and saturation. Because most of final control elements especially in chemical processes are subjected to saturation constraint and also due to lack of generaland practical control scheme to handle this limitation, our concentration will be focused on saturation nonlinearity. In this work, based on sliding mode control strategy, a control scheme for multi-input multi-state systems in the presence of input saturation is presented. Some numerical simulations are carried out to show the effectiveness of... 

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  

This project is aimed to design a controller for nonlinear systems that satisfy a prescribed performance while guaranteeing close-loop stability. To do this, the controller must be designed in such a way that the transient response of the system has had these performance indices and does not exceed them. These performance indices predefine some constraints for systems’ output.A comprehensive form for the model system, the unknown dynamics of the system, consideration of a variety of constraints on the system input, usage of the time-finite method for the residence time and consideration of just one tuning parameter to reduce the computation load, are among the other benefits for the proposed... 

This thesis addresses design of an adaptive tracking control of input-quantized strict-feedback fractional-order nonlinear systems with unknown control directions. The control design is achieved by using a hysteretic quantizer to avoid chattering. The main advantages of the proposed controller are: the fractional order is available for both commensurate and non-commensurate cases, the¬¬ controller design does not depend on the quantization parameters and some restrictive assumptions are relaxed. Additionally only one adaptive law has been used for the unknown control directions which leads to reduction of computational load. By utilizing the backstepping approach and based on the frequency... 

Due to the presence of a random variable in the process dynamics or due to the presence of measurement noise, many processes have stochastic in nature. Behaviors of these processes are different from the deterministic processes and therefore their controllers are also different. The aim of this research is to design adaptive controller for stochastic processes with a non-strict feedback structure and in the presence of input constraints. Also, the considered system has other limitations such as the unmeasured states, actuator failure, unknown dynamics and fixed time stability is desired. The input limitation can be caused by the limitation of the final control element, because the input... 

Anaerobic digestion of waste and wastewater has attracted researchers’ attention due to its important effect on reducing greenhouse gas emissions and reducing the level of environmental pollution and production of methane as a renewable energy source. This process is highly sensitive and can become unstable due to the presence of complex biochemical reactions and containing various types of chemical in it. In order to understand and improve the performance of this process, modeling and design of an appropriate control strategy is needed. ADM1 is the most accurate model for this process which is used in this study to describe and simulate the anaerobic reactor. Constrained and unconstrained... 

Anaerobic digestion of waste and wastewater has attracted researchers’ attention due to its important effect on reducing greenhouse gas emissions and reducing the level of environmental pollution and production of methane as a renewable energy source. This process is highly sensitive and can become unstable due to the presence of complex biochemical reactions and containing various types of chemical in it. In order to understand and improve the performance of this process, modeling and design of an appropriate control strategy is needed. ADM1 is the most accurate model for this process which is used in this study to describe and simulate the anaerobic reactor. Constrained and unconstrained... 

Continous blood glucose control has great importance for type 1 dyabetic patients. In this thesis, several types of controllers including: PI controller, model predictive controller base on state space model, linear model predictive controller base of linear input-output model and non-linear model predictive controller base of Hammerstein model have been used to regulate blood glucose of patients with type 1 diabetes. These models are identified using least squars method. Performance of these controllers is tested and the best one is introduced. For rejecting meal disturbances, a feedforward controller has been designed. Combination of feedback and feedforward controller would properly... 

In this study, an adaptive controller design for nonlinear fractional order systems in the strict-feedback form has been investigated. The system is subject to unknown dynamics, unmeasured state variables, quantized input and output, and input nonlinearity. A linear observer is used to solve the problem of unmeasured state variables. The fuzzy logic system is used to estimate the unknown functions, and instead of updating all the regressor weights, only the upper bound of their norms is updated, which significantly reduces the computational load. In the controller design, limitations due to the bandwidth of data transmission have been considered by applying quantizers in the input and output... 

The accurate fault diagnosing system design helps the process safety and also helps increasing the products quality of the process. In this project, the fuzzy system and neural network have been used for fault detection and diagnosis of a yeast fermentation bioreactor. In one case, parameters of membership functions are selected in a conventional manner. In second case, the optimal values of these parameters have been obtained using the genetic algorithm. In another case, the neural network system is used for fault detection. These three cases are compared based on their performances in fault diagnosis of a yeast fermentation bioreactor for three different conditions. The results indicate... 

In this work steady state and dynamic performances of quaternary distillation column sequences designed based on steady state and dynamic cost functions have been investigated. To quantify the dynamic performance, product loss due to disturbances has been considered in the objective function. In addition, variations of operating costs such as utilities have been considered in the objective function. To separate a quaternary mixture into four products, twenty two configurations have been used. It has been observed that the feed composition, disturbance frequency and magnitude affect the dynamic behavior strongly. To decrease the optimization computational load, a scheme that provides a... 

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... 

The aim of this thesis is investigating the approaches proposed for controlling switched systems and designing a controller for MIMO switched systems. The system under consideration is in strict feedback form with unknown dynamics, unmodeled dynamics, state-dependent delays and disturbances and input nonlinearity (saturation, backlash, dead-zone). In this work, the unknown dynamics are estimated by an intelligent approximator. The arbitrary switching law is assumed and for control purpose the switching instances are not required. The backstepping technique has been utilize for controller design and by using a nonnegative switching function and a common lyapunov function, the closed loop...