چكيده به لاتين
In recent years, drones have received much attention in military and civilian applications. Such aircraft, due to reduced production and maintenance costs, longer flight times, reduced radar detection probability, and reduced risk to flight crews, during military and civilian missions such as environmental and urban traffic control, etc. have a higher advantage over manned drones. One of the types of vertical drones are quadrotors. Research on quadrotors faces a variety of challenges. The issue of controller design is one of the most important and vital issues in the field of quadrotors.
due to the fact that the dynamics of quadrotors is highly non-linear and different disturbance forces are applied to the body of the quadcopter from the flight environment, the design of linear controllers is not a good way to perform an accurate and fast tracking and non-linear control methods should be used to eliminating external forces effects and various uncertainties and provide good performance. Among the nonlinear control methods, we can mention methods such as sliding mode and its different types, feedback linearization, back-stepping, and adaptive control, which combination of some of these methods gives better results. Among the mentioned methods, the sliding mode method is more popular due to the simplicity of the design process.
The issue of energy is another important topic in this area of research. From a control point of view, energy consumption is related to the control inputs of the system, which is also related to the control coefficients in the controller design process. Adjusting these control coefficients using intelligent methods such as methods based on fuzzy logic, neural networks and evolutionary calculations will reduce control inputs and thus reduce energy consumption, which will increase the maneuverability time of the quadrotor in the same power supply. And a reduction in the volume of the power supply is specified for a period of time.
The use of high-order sliding mode methods such as the terminal sliding mode method, the nonsingular terminal sliding mode and the super-twisting sliding mode, increasing the accuracy and speed of tracking and reduces the control inputs compared to the conventional sliding mode method. In this dissertation, we have designed a new control method based on high-order super-twisting sliding mode and its combination with adaptive fuzzy intelligent methods for quadrotters, which increases the accuracy and speed of tracking and reducing energy consumption compared to the methods used in previous researches in this area.
The simulation results show that the performance of the designed control system is very good compared to the methods used in previous research and it provides a significant reduction in energy consumption and also reaches a stable state in a finite time. The stability of the designed control systems has been proved by Lyapunov's theory. The simulation results are compared with the results of one of the authoritative articles in the field of quadrotor control for evaluation, which shows the improvement of the results in comparison with its results.
