Adaptive Trackers Based on Continuous Learning Theory |
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Authors: | Bershad NJ Merryman P Sklansky J |
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Institution: | University of California Irvine, Calif. 92664; |
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Abstract: | The theory of ?continuous learning? is applied here to the design of nonlinear sampled-data trackers. This theory provides a continuous-motion approximation of the discrete or sampled motion of the actual tracker. The theory prodicts the transient-response performance of the tracker as well as the mean-square errors caused by noise and statistical fluctuations in the signal. Numerical examples of first-order and second-order trackers designed by this technique are presented. These examples illustrate the adaptive behavior predicted by the technique. In one of these examples the trade-off between transient-response performance and the suppression of noise-induced tracking errors is demonstrated. |
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