Aerospace Science and Technology
Fatemeh Amozegary; Amir reza Kosari; Mahdi Fakoor
Abstract
The ever increasing demand for placing satellites in the geostationary orbit has caused the revision and change of the conventional mechanism of allocating orbital slots. Therefore, collocation approaches and station keeping of several satellites with a common position have been developed to improve ...
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The ever increasing demand for placing satellites in the geostationary orbit has caused the revision and change of the conventional mechanism of allocating orbital slots. Therefore, collocation approaches and station keeping of several satellites with a common position have been developed to improve the utilization of the capacity of the geostationary orbit. This, in turn, leads to an increase in the complexity and sensitivity of the modeling, guidance, and control processes. However, new restrictions are added to the problem of maintaining a common location, such as maintaining the minimum separation distance between satellites to prevent possible interference. Employing a collocation strategy is essential, especially for effective control of high-demand orbital regions that will lead to space congestion.Controlling the relative motion of satellites by maintaining a safe distance between them is the main rule in collocation. This article investigates the problem of the relative motion of satellites corresponding to collocation strategies. Then, the results are implemented and compared using a solution based on geometrical modeling of relative orbit and the concepts of spherical geometry. In this regard, the relative orbital elements of the two satellites are calculated using the presented relative motion modeling. Also, the relative position of the satellites is obtained. The case studies and evaluations confirmed that the inclination and eccentricity separation strategies are suitable options for meeting the fuel consumption requirements and providing more space for collocated satellites than other strategies.
Aerospace Science and Technology
Mahdi Fakoor; Hamidreza Heidari; Behzad Moshiri; Amir reza Kosari
Abstract
In this study, Adaptive Network-Based Fuzzy Inference System (ANFIS) is presented with sensor data fusion approach to estimate satellite attitude. The active sensors are sun and earth sensors. Satellite attitude dynamic, including attitude quaternion and angular velocities are estimated simultaneously ...
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In this study, Adaptive Network-Based Fuzzy Inference System (ANFIS) is presented with sensor data fusion approach to estimate satellite attitude. The active sensors are sun and earth sensors. Satellite attitude dynamic, including attitude quaternion and angular velocities are estimated simultaneously utilizing the measured values by the sensors. The Extended Kalman Filter (EKF) is employed to verify and evaluate the efficiency of the presented method. Additionally, the neural networks with Radial Basis Function (RBF) and Multi-Layer Perceptron (MLP) are also designed to prove the superiority of the proposed ANFIS network among the smart methods of sensor data fusion for satellite attitude estimation. Root Mean Square Error (RMSE) as a numerical criterion and graphical analysis of residues are utilized to evaluate the simulation results. The simulations confirm that the obtained estimations from ANFIS network have more accuracy in modeling of nonlinear complex systems compared to EKF, MLP and RBF networks. In general, using intelligent data fusion, especially ANFIS, reduces attitude estimation error and time in comparison to the classical EKF method.
Aerospace Science and Technology
Mahdi Fakoor; Seyed Mohammad Navid Ghoreishi; Mohamad Aminjafari
Volume 12, Issue 1 , March 2019, , Pages 27-37
Abstract
In this paper, a combination method has been developed by coupling Multi-Objective Genetic Algorithms (MOGA) and Finite Element Method (FEM). This method has been applied for determination of the optimal stacking sequence of laminated composite plate against buckling. The most important parameters in ...
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In this paper, a combination method has been developed by coupling Multi-Objective Genetic Algorithms (MOGA) and Finite Element Method (FEM). This method has been applied for determination of the optimal stacking sequence of laminated composite plate against buckling. The most important parameters in optimization of a laminated composite plate such as, angle, thickness, number, and material of each layer are considered in the proposed method. These optimization processes have done for 3 types of compressive loads and optimal stacking sequences and Pareto front for each kind of compressive loads are determined. Unlike estimation methods like response surface and simple analytic methods, in the proposed optimization algorithm, objective functions are calculated directly by FEM software which leads to precise results. The results of proposed algorithm are validated against existing data in literature. The effects of different boundary conditions and aspect ratio of plate on Pareto front in buckling of a laminated composite plate are also studied.
