Sharif Digital Repository

DC-DC switching convertors are power electronic circuits that have various applications nowadays. Quasi-resonant convertors are a kind of these convertors that are of great interest due to their simple structure and soft switching. The goal of controlling these convertors is to achieve constant output voltage while varying the input voltage and the load by choosing a proper switching frequency. Classic controllers show drawbacks in the case of high input voltage and load tolerance, and this nonlinear behavior of the systems results in some practical challenges. In this thesis, nonlinear predictive controller for quasi-resonant Buck convertors is designed. Having designed the linear... 

In industries there are many nonlinear processes which cannot be easily controlled with classical methods. Model predictive control is a useful method for nonlinear processes which not only has high efficiency, but also extension of this control to interferential multi variable case, with constraint on the controlled and manipulated variables and other problematic dynamic specifications such as slow dynamics and inverse response is very simple. Industrial polymerization processes are regarded as significant nonlinear processes. Optimization and control of polymerization reactors have considerable importance in process applicability and in economics. The molecular structure of polymer such as... 

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... 

The constrained nonlinear systems with large operating regions have attracted great attention due to their correspondence with the most practical systems. There are several tools such as gain scheduling and Nonlinear Model Predictive Control (NMPC) to control them. Gain scheduling, with ability to provide stability guarantees between the estimated stability regions overlapping each other and to cover a large space of the allowable operating range of the system, is an attractive practical approach to control the systems with large operating regions. But this strategy do not account for constraints explicitly by online optimization. On the contrary, NMPC handles constraints on the manipulated... 

A group of vehicles are contributed to follow static or dynamic targets in a cooperative target tracking problem. The vehicles estimate the future location of dynamic targets based on the information they receive from other vehicles and targets. Noting to these estimations, the vehicles are able to decide the best movement toward the targets. Various control methods have been presented to solve different problems of target tracking which the majority of them proposed optimal control solutions. A new approach to the problem of tracking dynamic targets via cooperative multi-vehicle systems under the receding horizon control of the vehicles is proposed in this dissertation. A receding horizon... 

In the industry, there are nonlinear processes that can not be controlled with classical methods. Also, there are many processes that are more than one controlled variable that with classical methods, the design of a multiple input - multiple output controler is very difficult for them as well as the constraints on the inputs and outputs of the process exist, using classical controllers will be far more difficult. A model-based predictive control method for controlling nonlinear processes is useful in addition to having very high efficiency, extended to multi-mode interference together with constraints on the control variables and other controlled Problem with dynamic properties such as... 

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... 

A distributed model predictive control with two-layer structure for communication is presented in the present thesis for elimination of the propagation and amplificationphenomenon of the upstream transient errors in automated irrigation networks. This phenomenon results in the saturation of actuators in long automated irrigation channels and therefore it results in significant reduction in the quality of service of the irrigation network. Hence, the elimination of this phenomenon in long irrigation channels is necessary, in which a distributed model predictive control with two-layer structure for communication is presented in the presentthesis for elimination of this phenomenon. Feasibility,... 

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... 

The application of fuel cell systems as sources of clean energy production is common. Control, performance optimization, design, manufacturing and the operation management are considered as significant research interest of the fuel cell in academic circles. A major problem, at least in the advanced model-based control, is the slowness of solving the nonlinear multi-scale model (time). One option would be using the black-box neuro-fuzzy models. Then if the predictive controller is used for this distributed system, calling the output of neuro-fuzzy model allocated a negligibility proportion in time of calculations during the optimization. In this project, the data generated by a dynamic... 

In this study, the two rigid body modelling of a Coanda air vehicle (one rigid includes rotor and propeller and the second rigid includes the other parts of it) has been developed using Newton’s and Euler’s laws, and its motion was simulated in climb and forward flight conditions. Air vehicle propulsion force and moment have been modelled by employing the blade element momentum theory. In order to model the forces acting on the air vehicle, the drag force has been estimated by the results of analytical and computational fluid dynamics methods for the case of climb flight and by using experimental data of a cylindrical body for the forward flight. For modelling the control surfaces of this... 

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... 

Many industrial systems have on/off actuators. Traditionally, these systems are controlled using traditional control methods, like PID controller. The performance of this controller is not ideal for these systems, especially in term of transient response and power consumption. Due to the large number of constraints for these systems, to improve the performance of them, it is necessary to use the model predictive control technic. The decision variables of these systems are integer, hence it is necessary to develop the model predictive control method based on integer programming, which is the subject of this thesis. The main challenge in the development of this model predictive control method,... 

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... 

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... 

The following thesis is concerned with the control of automated irrigation channel using model predictive control in order to eliminate upstream transient error propagation and amplification phenomenon. It is illustrated in the literature that one way of dealing with this phenomenon is to solve a constrained optimization problem at each receding horizon. However, this problem becomes infeasible for automated irrigation channels. Several methods in the literature have been proposed that exploit terminal constraints to guarantee the feasibility of this problem. Finding these constraints, however, is extremely time-consuming as well as impractical for large-scale automated irrigation channels.... 

No one bears thinking about undergoing a surgery by an unexpirienced surgeon, the consideration of which implies the prominence of effective surgical trainings. The advent of utilizing haptic interfaces as a novelty in this field has led to a more promising surgery education. These haptic interfaces consist of three communicating parts namely: operator’s hand, haptic robot, and tissue virtual environment. Design and implementation of a proper controller in order to stabilize the haptic interface during surgery simulation, with acceptable transparency, is still novel an otherwise challenging research field. In this thesis we consider an appropriate nonlinear model for both virtual tissue as... 

Accurate and fast position controlling is an important issue in today’s industrial needs. Drives used for position control require fast dynamics on speed control. Cascade linear controllers have sluggish response due to bandwidth limitations on speed and current loop. These structures limit the dynamics above all in high power applications where the switching frequency is low. In this thesis, deadbeat direct speed control is proposed, which overcomes limitations by cascade loops resulting in high-speed control dynamics. This approach uses a model of the plant to generate the control signals. According to measured speed and currents, the controller specifies the best voltage vector in order... 

The purpose of this study is the implementation of multi-model predictive control (MMPC) approach for the co-polymerization system of methyl methacrylate - vinyl acetate. Simpler development of local models and controllers and also convenience of understanding the model and controller structure are the main reasons for using this approach. In the first step, RGA analysis has been used for pairing input and output variables. Then the performance of PI controller on the system has been investigated. For designing model predictive controller (MPC) the nonlinear model has been linearized at operational point and the controller has been designed in MPC toolbox of MATLAB software R2013a. In the... 

Anaerobic digestion is a useful process that is very important, addition to producing methane as energy source, it can be used for treatment of solid waste and sewage sludge. This process due to the presene of chemical and biological reactions and abundant chemical species, is very complicated and sensitive, so it is very unstable against any kind of change. as for the large importance of the process, we need control and optimization. In order to improving the performance of the process and increasing biogas and methane production, we should control and optimize the process. ADM1 is principal and the most accurate model for this process, a variety of reduced order models used to design...