Adaptive Trackers Based on Continuous Learning Theory

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.     

Comparative analysis of energy storage media and techniques

Techniques for storing and converting energy from one form to another are examined. The parameters of interest are storage density (in terms of both energy and power), conversion efficiency, and number of steps in the conversion process. The techniques compared are electrostatic, magnetic, inertial, chemical, thermal, and nuclear. Each technique for storage is discussed in terms of the ease with which the energy can be converted to electricity for powering lightweight compact power systems for a variety of uses. The storage density associated with the various mechanisms spans an enormous range (~0.5 MJ/kg to ~10⁵ MJ/kg). The impact upon time-to-refuel within the context of mobile tactical army applications is discussed