Conference Papers-Iterative Learning

Communications & Networks

Image & Signal Processing

Load Balancing

Microwave Propelled Sail

Randomized Algorithms

Time Delay

Multi-Agent Coordination

Engineering Education

Iterative Learning

Neural Networks

Robust Control

Various

Note: The papers on this website may differ from the published versions, both in format and in content.

1. C. T. Abdallah, V.S. Soualian and E. Schamiloglu, "Toward “Smart Tubes” Using Iterative Learning Control", IEEE Trans. Plasma Sci., vol. 26, pp. 905-911, 1998.   [pdf]

   Abstract: In this paper, we present our progress toward designing a “smart” high-peak power microwave (HPM) tube. We use iterative learning-control (ILC) methodologies in order to control a repetitively pulsed high-power backward-wave oscillator (BWO). The learning-control algorithm is used to drive the error between the actual output and its desired value to zero. The desired output may be a given power level, a given frequency, or a combination of both. The learning-control methodology is then verified in simulation. This methodology is applicable to a wide variety of HPM sources.




2. V.S. Soualian, G.T. Park, C. T. Abdallah, and E. Schamiloglu, "Iterative Learning Control Applications to High Power Microwave Tubes",    [pdf]  [ps]

   Abstract: In this paper, we present a “smart” high-peak power microwave tube, by implementing iterative learning control methodologies to control a repetitively-pulsed, high-power, backward wave oscillator. The learning control algorithm is used to drive the error between the actual output and its desired value to zero. The desired output may be a given power level, a given frequency, or a combination of both. The learning control methodology is then experimentally verified.