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The Smart Crane Ammunition Transfer System (SCATS) is designed to handle, deliver, and reload missiles/ammunitions in the battlefield. The system objectives are as follow: faster missile reloading, decreased utilization of manpower, increased operator safety, reduced missile/munitions damage, reduced operator skills and training, and increased material flow. In this paper, the smart crane ammunition transfer system is introduced and discussed, including the crane, the hydraulic system, the control system, and the development environment. The emphasis is on the design, analysis, and implementation of the SCATS control system. State-of-the-art engineering techniques, such as robotic control, trajectory generation, sensory processing and task planning, are also addressed as to the way in which they will enhance the SCATS system performance and functionality as applied to the automation of complex material handling and resupply actions.

A reference architecture model of a typical fire control system has been established with the Real-time Object-Oriented Modeling (ROOM) environment, ObjecTime. An external graphics user interface (GUI) has also been developed to communicate with the reference architecture, thus making the reference architecture an ideal tool to test a specific design based on the architecture implementation. The GUI also communicates with an independent ballistics calculation program to send the target parameters and receive the ballistics calculation results. The ObjecTime model, the GUI, and the external ballistics calculation program constitute a demonstration system for the fire control reference architecture.

In this paper, the problem of estimation and prediction of the projectile trajectory, MET data, and the impact point is formulated within the extended Kalman filtering framework. Factorized implementations of extended Kalman filtering, smoothing, and prediction algorithms are presented. Different wind models are discussed. The algorithms are demonstrated through simulation.

Tactical ballistic missiles (TBM) target may experience severe spiral maneuvers as they reenter the earth's atmosphere due to a configurational asymmetry. To hit these targets, the interceptor must possess extremely fast maneuver response characteristics. Before 10 secs to go optimal integrated guidance and control (OIGC) is slightly better than a conventional autopilot. From 2 to 10 secs OIGC is much better than a conventional autopilot in closing up trajectories. However, with 2 secs to go, OIGC uses up full authority and with the aerodynamic surfaces alone may not catch the tactical ballistic missile target. Therefore, there is a need for thrusters. In this paper, a blending mechanism of optimal integrated guidance and control (OIGC) and fuzzy logic controlled thruster is developed for a skid-to-turn missile to improve the missile interception performance. OIGC is an innovative approach to designing guidance and control laws.

In this paper, an intelligent autonomous deck landing system is designed for an Unmanned Air Vehicle (UAV). First, the design specifications and requirements are identified for the design of UAV flight control and landing systems. Then the longitudinal models of the UAV are established for the design of an autonomous UAV landing system. The system is designed using fuzzy logic, which is able to provide longitudinal stability and to improve the tracking performance. Simulation results show that the developed landing control system has very good robustness against aerodynamic uncertainty, and good fault tolerance against actuator failures. This indicates that the intelligent landing system has the ability to stabilize a damaged aircraft without knowledge of the types of fault or system parameters. Wind disturbances are also investigated by using the turbulence model for the ship-landing environment.