ANS is committed to advancing, fostering, and promoting the development and application of nuclear sciences and technologies to benefit society.
Explore the many uses for nuclear science and its impact on energy, the environment, healthcare, food, and more.
Explore membership for yourself or for your organization.
Conference Spotlight
2026 ANS Annual Conference
May 31–June 3, 2026
Denver, CO|Sheraton Denver
Latest Magazine Issues
Mar 2026
Jan 2026
Latest Journal Issues
Nuclear Science and Engineering
April 2026
Nuclear Technology
February 2026
Fusion Science and Technology
Latest News
State news: Microreactors, legislation, executive orders, and more
Discussions and actions on nuclear energy have penetrated several state capitol buildings, congressional hearings, and industry gatherings across the United States this month, including in Alaska, Connecticut, Louisiana, Massachusetts, Minnesota, and New York.
Roman Shaffer, Weidong He, Robert M. Edwards
Nuclear Technology | Volume 147 | Number 2 | August 2004 | Pages 240-257
Technical Paper | Nuclear Plant Operations and Control | doi.org/10.13182/NT04-A3529
Articles are hosted by Taylor and Francis Online.
Design applications for robust feedback and optimized feedforward control, with confirming results from experiments conducted on the Pennsylvania State University TRIGA reactor, are presented. The combination of feedforward and feedback control techniques complement each other in that robust control offers guaranteed closed-loop stability in the presence of uncertainties, and optimized feedforward offers an approach to achieving performance that is sometimes limited by overly conservative robust feedback control. The design approach taken in this work combines these techniques by first designing robust feedback control. Alternative methods for specifying a low-order linear model and uncertainty specifications, while seeking as much performance as possible, are discussed and evaluated. To achieve desired performance characteristics, the optimized feedforward control is then computed by using the nominal nonlinear plant model that incorporates the robust feedback control.