الفهرس 
INTRODUCTIONOnly 14 pages are availabe for public view
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Abstract
The continuous development of the fighting aircraft industry in terms of range, speed and maneuverability must be encountered by a continuous development of the missile guidance system to achieve the minimum miss distance when shooting the target. The miss distance is defined as the distance between the calculated and the actual interception point between the missile and the target. The optimum performance of the guidance system is achieved when nullifying the Miss distance. In this study, a genetic algorithm is employed to develop the guidance process to achieve the minimum miss distance and three techniques are considered. The first technique is devoted to optimizing a dynamic navigation ratio of guidance law. This optimization provides a bounded target interception utilizing six degrees of freedom control to improve the intercepting accuracy of launch vehicles. It is performed for two guidance laws, the proportional navigation and the differential geometry under the influence of target heading, altitude, and target maneuvering capabilities. The simulation of missile-target scenario, which enhanced by genetic algorithm, is running multiple times to check all forms of gain until achieving the optimum performance. The second technique uses a smooth variable gain rather than multiple quantized levels. This form enhances the overall performance and eliminates the undesired effect of a sudden change in gain. The variable gains are formulated by selecting eight points and complete the curve by interpolation. A genetic algorithm is utilized to optimize the selection of these points. The average values and standard deviation of miss distance for all genetic algorithm individuals are calculated to measure the performance of guidance law. Also, the two guidance laws are investigated to determine which is better at different conditions. The third technique utilizes Kalman filter as a target estimator. A Kalman filter performs well at low noise, but increasing noise causes significant errors and performance degradation. Therefore, tuning factors are utilized to adjust Kalman filter to overcome noise. They are selected using genetic algorithm depending on target heading. The aim of this selection is to compensate the effect of noise, decrease the miss distance, and expand the effective range which increases the probability of kill. Stewart platforms have several applications like flight simulation, machine tool and crane technology, underwater technology, satellite dish positioning, mechanical bulls, telescopes and orthopedic surgery. In this research a small platform was built to represent the missile’s motion. A six-degree-of-freedom model used in this research was also used to send the movements data of the missile including linear motion and rotation motions in the three axes. A serial communication channel was built between the model and Stewart platform.