This paper investigates the trajectory prediction and dispersion for unguided fin stabilized artillery rocket in order to explain the importance of the rocket production accuracy and the benefit of using guided rockets. The total dispersion results mainly from three effects. The first is the dispersion due to rocket production inaccuracy, which includes propellant mass, composition inaccuracy, rocket total mass, axial and lateral moments of inertia and resultant center of gravity. The second dispersion during boosting phase which includes launcher deflection, missile tip-off from the launcher, thrust and fin misalignments, and atmospheric disturbances such as tail wind, cross wind, and gusts. While the third is the dispersion during free-flight phase that is due to the fluctuations in wind profile. In this study, a trajectory calculation using a 6-DOF model was developed and applied for a typical artillery rocket, the 122 mm artillery rocket, at different mass and flight properties to predict the trajectory parameters and dispersion.
Any trajectory calculation method has three primary sources of errors, which are model error, parameter error, and initial state error. In this paper, based on initial projectile flight trajectory data measured using Doppler radar system; a new iterative method is developed to estimate the projectile attitude and the corresponding impact point to improve the second shot hit probability. In order to estimate the projectile initial state, the launch dynamics model of practical 155 mm self-propelled artillery is defined, and hence, the vibration characteristics of the self-propelled artillery is obtained using the transfer matrix method of linear multibody system MSTMM. A discrete time transfer matrix DTTM-4DOF is developed using the modified point mass equations of motion to compute the projectile trajectory and set a direct algebraic relation between any two successive radar data. During iterations, adjustments to the repose angle are made until an agreement with acceptable tolerance occurs between the Doppler radar measurements and the estimated values. Simulated Doppler radar measurements are generated using the nonlinear sixdegree-of-freedom trajectory model using the resulted initial disturbance. Results demonstrate that the data estimated using the proposed algorithm agrees well with the simulated Doppler radar data obtained numerically using the nonlinear six-degree-offreedom model.
This paper investigates the dispersion for unguided spinning projectile in order to explain the importance of the projectile production accuracy and the benefit of using guided projectiles. The total dispersion results mainly from the production inaccuracy of: (1) gun tube which can be shown in projectile's launching problems (muzzle angle, and muzzle pitching and yawing rates), (2) propellant which can be shown in projectile's muzzle velocity and muzzle spinning rate and projectile which is the projectile total mass, axial and lateral moments of inertia, and resultant center of gravity. The other causes are occurred due to free flight portion of projectile's trajectory which may be divided to: launching problems (vibration of launch tube), wind velocity and direction (wind profile). In this study, a trajectory calculation using a 6-DOF model was developed and applied for 155 mm M107 projectiles at different projectile and flight properties.
Transfer matrix method for multibody systems (MS-TMM) is a rife method to multi-rigid-flexible-body systems dynamics model deduction due to that there are no needs to establish the global dynamics equations of the system. Its basic idea is transferring a state vector between the body input(s) and output(s); this idea is close to the linear theories in control analysis and design. In this paper, three controllers' parameters tuning techniques for the proposed system model using MS-TMM are utilized; one technique is applied to get the stability regions via the frequency response of MS-TMM derived model. Another technique considers a classical PID controller design through the analysis of step input response of the system, and the last technique can be applied in both time and frequency domains if the model has a known mathematical model. A car suspension system is considered to represent modeling and tuning problems. In-depth study of MS-TMM with control techniques and defining the controllers' parameters stability regions provide an opportunity to formulate a relationship between MS-TMM and control design for novel control applications due to the powerful strength of MS-TMM dealing with more complex problems of the controlled multibody systems.
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