Data processing: artificial intelligence – Neural network – Learning task
Reexamination Certificate
2001-02-21
2003-04-01
Starks, Jr., Wilbert L. (Department: 2121)
Data processing: artificial intelligence
Neural network
Learning task
C701S004000
Reexamination Certificate
active
06542879
ABSTRACT:
BACKGROUND OF THE INVENTION
1. Field of the Invention
The present invention relates generally to trajectory control of objects, and more particularly, to neural networks used in trajectory control of objects.
2. Description of Related Art
There is typically a desire to improve the performance of a missile by increasing its speed, range, and maneuverability without violating physical or functional constraints placed on the system design. Extensive past studies aimed at optimizing all aspects of a missile's trajectory commands for a specific scenario have been of limited value. The situation has been complicated by a desire to optimize performance in multiple scenarios (e.g., a desire for a missile to take the quickest path to its target and minimize “miss distance” at intercept, all the while meeting minimum flight control/maneuverability requirements). In some situations, multiple goals such as these can appear contradictory to the analyst, and often have defied the definition of a theoretically optimum solution, especially, for the case of a maneuvering/evasive target, where the missile must adaptively and continuously arrive at optimum solutions after launch and during missile flight.
Another problem in the implementation of optimized trajectory shaping in guided missiles has involved the immense scale of the problem. The numerous variables involved in the characterization of a specific tactical scenario (e.g., launcher and target locations, velocities and postlaunch maneuvers) contribute to enormously complex physical relationships, which are further complicated by varying uncertainties in associated measurements of these factors.
Previous approaches to tactical decision making in guided missile design have typically taken one of two courses: 1) simplification of the problem to a select (and fixed) set of possible trajectory shaping “schedules” based on roughly-defined input criteria; or 2) an attempt to simulate possible outcomes of different trajectory decisions in “real-time” using on-board missile processing equipment, with the best performing flight path(s) selected from all of the simulation runs conducted. Prior studies have shown that there are significant drawbacks to each of these approaches.
The first approach, for example, while realizable in a constrained guided missile electronics package, produces less-than-optimal performance in many application scenarios. Such simplification of a problem known to have multidimensional relationships and complexities is, effectively, a compromise, and, as such, any goal of optimized performance in widely varying scenarios will also be compromised in its use. This approach reduces complex (and sometimes little-understood) physical phenomena into simplified “on-the-average” equations or “look up” tables in a missile's software or hardware control devices, from which simple interpolation techniques are employed. This, in turn, has resulted in compromised performance in many of the infinite number of mission scenarios possible for such missiles. Nonetheless, this approach has typically been employed in existing guided missiles, with the hope that sufficient testing and analyses can be conducted to identify where significant shortfalls in performance may exist.
Use of the second approach mentioned (i.e., on-board simulation and iterative optimization for the specific launch scenario in which the missile is used) has been effectively prohibited by incapacity of on-board data processing equipment and the tight time frame in which tactical decisions are required. High fidelity simulation of complex in-flight guided missile dynamics taxes even highly-powered ground-based laboratory computer systems. Such missile simulation runs often require a comparable time to execute to that involved in actual missile flight. Therefore, even if on-board tactical data processing equipment was comparable in speed and memory capacity to that typically used in laboratory simulations (which it typically is not), simulation of even one possible outcome would require the entirety of a missile's flight to execute. Clearly, sequential simulations are very difficult to reveal an optimal solution in “real-time”.
There is, therefore, a need for a missile to have improved performance obtainable through continually adapted maneuvering controls as appropriate for optimal achievement of multiple kinematic performance objectives specific to each tactical situation.
SUMMARY OF THE INVENTION
In accordance with the teachings of the present invention, an apparatus and method are provided for controlling trajectory of an object to a first predetermined position. The apparatus has an input layer having nodes for receiving input data indicative of the first predetermined position. First weighted connections are connected to the nodes of the input layer. Each of the first weighted connections have a coefficient for weighting the input data. An output layer having nodes connected to the first weighted connections determines trajectory data based upon the first weighted input data. The trajectory of the object is controlled based upon the determined trajectory data.
Additional advantages and aspects of the present invention will become apparent from the subsequent description and the appended claims, taken in conjunction with the accompanying drawings in which:
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Biggers James E.
Finn Kevin P.
McClain, Jr. Richard A.
Schwartz, II Homer H.
Harness & Dickey & Pierce P.L.C.
Raytheon Company
Starks, Jr. Wilbert L.
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