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Adaptive Control

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MATLAB Machine Learning

Abstract

Consider a primary car that is driving along a highway at variable speeds. It carries a radar that measures azimuth, range, and range rate. Many cars pass the primary car, some of which change lanes from behind the car and cut in front. The multiple-hypothesis system tracks all cars around the primary car. At the start of the simulation there are no cars in the radar field of view. One car passes and cuts in front of the radar car. The other two just pass in their lanes. You want to accurately track all cars that your radar can see.

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References

  1. K. J. Åström and B. Wittenmark. Adaptive Control, Second Edition. Addison-Wesley, 1995.

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  2. A. E. Bryson Jr. Control of Spacecraft and Aircraft. Princeton, 1994.

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  3. Byoung S. Kim and Anthony J. Calise. Nonlinear flight control using neural networks. Journal of Guidance, Control, and Dynamics, 20(1):26–33, 1997.

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  4. Peggy S. Williams-Hayes. Flight Test Implementation of a Second Generation Intelligent Flight Control System. Technical Report NASA/TM-2005-213669, NASA Dryden Flight Research Center, November 2005.

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© 2017 Michael Paluszek, Stephanie Thomas

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Paluszek, M., Thomas, S. (2017). Adaptive Control. In: MATLAB Machine Learning. Apress, Berkeley, CA. https://doi.org/10.1007/978-1-4842-2250-8_11

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