نشریه مهندسی هوانوردی
سال بیست و یکم شماره 2 (پاییز و زمستان 1398)

It is necessary to maintain the capital of the country, rational and planned utilization, evaluation and maintenance of machinery and equipment in due time. Therefore, this research aims to prioritize the factors affecting the success of the maintenance program in the NEHAJA. This research is a practical and descriptive survey method with a quantitative approach. The statistical population of the study is the maintenance experts of the army of the Republic of Iran with a protective factor, 75 of them were selected as statistical sample. To analyze the data, T-test, Fuzzy ANP and Fuzzy DMF were used. The research findings indicate that "human resources", "capital resources", "economic factors", "employer human resources" and "age of the aircraft" affect the success of the maintenance program. Among these factors, "human resources", "human resources employer", "capital resources" and "age of the aircraft" have a great influence on "economic factors", and finally, "agents economics" rank first, and "employer human resources", "capital resources", "aircraft age" and "human resources” are next. In order to save financial resources and the specific economic conditions of the country (economic and political conditions), which makes it impossible to buy the aircraft, the issue of maintenance and repair is more and more to be considered and the latest scientific findings.

Vibratory energy in direct contact with different members of the body, in a certain frequency range, can be risky. On the other hand, the maneuvers that the pilot conducted during the flight and the sudden accelerations of g entering the plane on the head and neck, the spinal cord and other organs of the body have adverse effects and disrupt the physiological and psychological actions of the pilot. The first, in this research by choosing a suitable model of the human body and then by extracting the motion equations, using the MATLAB software, the displacement, velocity and acceleration equations for each member of the body are obtained. The new work in this research is putting on the model of seat with cushion made of  foam, cushion made of viscoelastic and with cushion made of viscoelastic despite the pilot's seat suspension system that has a non-linear springs and dampers. The results indicate that at high acceleration of g, the pilot's suspension system has the best performance in damping and absorbing the energy of the system. For small movements that at low frequencies in the range of 0 to 30 Hz are occurred, the seat suspension system is not responding and to check this state, we must examine the functions of biodynamics and plotting them in two states of the body in sitting position and body in sitting position on a foam pad. In this case, the results indicate that in the apparent mass diagram, the use of cushion made of foam caused peak shift in this chart from a frequency in the range of 5 Hz to a frequency in the range of 13 Hz. Therefore, the presence of cushion for health is absolutely necessary.

In this paper, two points guidance law of a missile is optimized based on the gravitational search algorithm. For this purpose, first, a five-degree-of-freedom equations of the missile and target are modeled. The proportional guidance law is, then, simulated to track the target. In the next step, the parameters of the law guidance are optimized using the gravitational search algorithm. Finally, the movement path of the missile and target on the horizon and vertical plane, acceleration commands, as well as the miss distance are shown. Also, the effect of axial acceleration compensation, gravitational compensation, updated frequency on the acceleration commands, the seeker's range as well as the maximum rate of seeker are investigated on the guidance law.

In this paper, a sliding mode guidance (SMG) law for a smart projectile with its optimization is presented. Due to the importance of acceleration of maneuvering targets due to their complex and inaccessible nature, an estimated upper bound of the target acceleration is considered as a disturbance in the formulation of the proposed law. Moreover, in order to obtain intercepting the target in a finite time of flight, a new definition of the sliding surface is presented as the relative distance between the projectile and the target multiplied by the line of sight (LOS) angular rate. In order to increase the efficiency of the interception, the design parameters of the proposed law are optimized based on a multi-objective genetic algorithm (MOGA) using an objective function with a combination of the control effort, the miss distance and the time of flight criteria. Therefore, the proposed robust guidance law has the optimality properties. The simulation results are caused to decrease miss distance, decrease control effort, and decrease the time of flight, which indicates the effectiveness and accuracy of the proposed law compared to other corresponding methods.

Precise guidance and navigation is one of the necessities of every moving vehicle in the transportation industry. Different methods of navigation has been used to determine exact location of the vehicle in each moment. Inertial navigation is a newton-based method that provides position of the vehicle regardless of any external communication equipment. Inertial navigation is always subject to different disturbing errors that consistently reduce the performance of the system, therefore, for long-term navigation purposes, there should be at least one navigation assisting system to maintain positioning accuracy. Consequently, a GPS/INS data fusion using a Robust Extended Kalman Filter (REKF) is investigated in this paper. When vehicles enter an area with a signal jammer, GPS position would be unavailable, and, filter observations will not be updated. Thus, a trained nonlinear neural network is used to predict position in this scenario. In order to test the algorithm in real-world circumstances, a custom designed board with military standards is employed. The results show about 70% of position improvement towards each axis. The proposed algorithm has improved the position accuracy in GPS/INS integrated system in defined scenario.

A usual target-tracking problem is the type of state estimation problem. The target states must estimate from noisy, false measurements and dynamic state variable such as position, velocity and acceleration. State estimation needs algorithms called filter, which based on Bayesian estimation. The tracking successful key is in extracting applicable, useful data from observation about target states. Certainly, having a proper model of target dynamics and measurement will make it much easier. Estimation filters and most of other algorithms used for estimation based on model since, there is knowledge about target dynamics. In this paper, we investigate and compare various target tracking models for aerial target tracking using visual sensor and accurate laser finder. The results of this study show that Jerk and Markov model have better performance relative to other dynamic models.