جستجوی مقالات مرتبط با کلیدواژه « کوادروتور » در نشریات گروه « برق »

Multi-agent systems are systems in which several agents accomplish a mission in a cooperative manner. In this paper, a novel idea for the construction of a movable runway platform based on multi-agent systems is presented. It is assumed that an aerial agent (quadrotor) decides to make an emergency landing due to reasons such as a decrease in energy level or technical failure, while there is no suitable platform for landing or the agent is not able to reach another place for landing. The goal is to create a specific formation pattern by a group of mobile robots that are smaller than the aerial agent, so that it can land on them. Each of the mobile robots is equipped with flat grid landing pad in its upper part so that when the robots approach each other and form a specific geometric arrangement (such as a pentagon), the landing pads are connected to each other and create a wider platform for landing. Cooperative control of agents (from aerial agent control to mobile robot formation control) is the main goal of this article, which is presented in different dynamic models under directed graph along with proof of Lyapunov-based stability analysis.

In this paper, a method is proposed for the control of a quadrotor based on sliding mode control by using Chebyshev neural networks. The proposed approach is a combination of the sliding mode controller and the Chebyshev neural network approximator that the neural network weights are tuned in real-time by using robust adaptive techniques. In this research, the dynamic model of the quadrotor is divided into two subsystems for the purpose of the position and orientation tracking control: a fully-actuated subsystem and an underactuated subsystem. For the former, the sliding surfaces are designed by using one state variable, and for the latter, the sliding manifolds are defined by a linear combination of two state variables. In this paper, the system stability is analyzed by Lyapunov theory-based techniques and the accuracy of the controller performance will be illustrated by the simulation results.

Quadrotor is a body floating in space with six degrees of freedom. The purpose of this article is ideal path tracking and control of a quadrotor in presence of payload disturbance and uncertain inertia matrix proposition. Control and ideal path tracking have been applied by a back-stepping sliding mode control. To eliminate the payload disturbance, a coefficient factor has been considered in the altitude controller design. Given that mass have a direct impact on inertia, the dynamic of payload compensation coefficient estimate and inertia parameters have been calculated using the adaptive method based on Lyapunov theory to eliminate the effects of these disturbance and uncertainty. Finally, simulation results have been presented in order to investigate the performance and robustness of the designed controller in the face of payload disturbance.

A Quadrotor helicopter is an unmanned aerial vehicle (UAV). This vehicle has attracted lots of researchers’ attention because of its unique abilities such as being an under-actuated system, vertical take-off and landing, spot movement, more degree of freedom (DOF) and military and non- military functions. Because of nonlinear and complex dynamic, modeling and controlling this vehicle is one of the most challenging areas in control engineering. In this paper modeling of a Quadrotor will be described using Newton-Euler equations. Stabilizing and controlling of altitude and its attitude are done by three controller including classic PID, Fuzzy- PID and Neural- Fuzzy based on PID. Performances of these controllers are analyzed in the presence of disturbances and mass uncertainties. The main aim of this paper is designing an intelligent PID algorithm which is made by combining fuzzy logic and neural system and it will introduce a Neural- Fuzzy controller which is based on PID. Simulation results are presented by MATLAB software.