Sharif Digital Repository

In this thesis, black-box identification, designing and implementing an iterative learning controller for the quadcopter was performed. Initially, the open-loop quadcopter system is unstable, so for black-box identification, a controller must first be implemented to stabilize it, but since no model is available from the system, the controlling parameters of the stabilizer through a proportional-integral and a proportional controller are executed as trial and error. To identify the roll and pitch models, the quadcopter is carried out using a radio controller and the measurements are saved during flight. Different models and methods are used to black-box identification, and finally the best... 

Heating, Ventilation and Air-Conditioning (HVAC) systems of buildings consume an excessive amount of energy and emit even more amounts of carbon, all around the world. Rule-Based Control (RBC) algorithms, which switch the facilities on and off according to the measurements of the building’s sensors, are the most frequently utilized controllers in HVAC systems. Due to the conservative settings of the comfort-zone in RBC strategies, energy consumption increases by a large amount. One of the most conventional ways to improve the energy efficiency along with providing the thermal comfort of the occupants of the building, is model predictive control (MPC) algorithms. In order for MPC to work... 

In today's world, mobile robots have many applications in defense, transportation and industry. A robot may not be able to handle a mission alone or there may be different roles to perform a mission that a robot alone cannot perform, so the need to work with team robots is felt to the Necessary that by development Robot Technology and Advances in Communication, Microelectronics, Computing Technology, and Multi - Factor Expansion, robotic systems are widely used in theoretical research due to their flexibility, robustness, and scalability. In this research, robots are controlled in a coordinated manner as a team. In this research, algorithms were developed so that in a two and... 

One of the crucial ways to reduce the energy costs of buildings is to improve the energy efficiency of HVAC systems. Heating, Ventilation, and Air Conditioning (HVAC) refer to the systems used to adjust the heating and cooling within a building. Control of these systems has great importance due to their excessive energy usage. Various control methods have shown a potential for considerable savings in building operation costs. In this research, a Model Predictive Controller (MPC) is applied to perform optimal control actions. MPC opens up numerous opportunities to improve energy efficiency in the operation of HVAC systems because of their capability to consider constraints, prediction of... 

Energy management in buildings play an important role in minimizing the global energy consumption. Providing an optimal temperature in buildings and workplaces is a significant step toward the energy management, regardless of the local climate. Buildings account for 20-40% of the world’s total energy consumption, and this consumption is increasing in developed countries at 0.5-5% per annum.In various studies, energy consumption potential has been investigated using model predictive control (MPC) and system identification.In this paper, the building system is modeled as a gray-box model in which the formulas are developed using the heat transfer equation and the solar radiation heat is... 

Buildings account for more than 30% of the world’s total energy consumption. Among building end-uses, air conditioning and in particular cooling systems have a major share of more than 50%. Therefore, design of optimal controllers for AC systems has become increasingly important. Classical and model-free control methods typically lack the ability to optimize energy consumption. On the other hand, model-based optimal control methods rely on precise modeling, which is difficult to acquire due to the complexity of the AC system dynamics.In recent years, deep reinforcement learning has become a popular choice for optimal control of systems with complex dynamics. In this thesis, a deep... 

In this research, we have examined the efficiency of solar tower power plant. The solar tower power plant is one of the most important types of solar power plants that have been noticed due to the possibility of reaching high temperatures and good thermal efficiency. A concentrated solar tower power plant is one of the ways to convert solar radiation into electricity. In this process, the cold water at the top of the tower turns into hot water and then turns into steam, and from there it is given to the generator, which produces electricity. In this type of power plant, there are a large number of mirrors, which are called heliostats, and they are controlled separately and reflect the... 

In recent years with the development of industrial automation, artificial intelligence, and the coming of the fourth-generation industrial revolution, making robots intelligent and solving old challenges in non-linear systems in order to make human life easier has always been the point of view of researchers. Flight systems are always considered to be one of the most nonlinear systems. In linear systems, a PID controller can be easily designed and implemented; But in non-linear systems, because the set point is constantly changing, the PID gain must be manually adjusted by the operator, which is almost impossible in practice; Therefore, finding a fast and efficient way to solve this...