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 Nuclear Energy Conference & Expo (NECX)
August 24–27, 2026
Dallas, TX|Hilton Anatole
Latest Magazine Issues
Jun 2026
Jan 2026
2026
Latest Journal Issues
Nuclear Science and Engineering
July 2026
Nuclear Technology
Fusion Science and Technology
May 2026
Latest News
Breaking ground on a new approach to construction
The drive to Kairos Power’s reactor demonstration site in Oak Ridge, Tenn., is not only scenic—it’s historic. Nearly 85 years ago, roughly 30,000 construction workers transformed orchards and farmland into a key Manhattan Project site. Depending on your route, you may pass by one of the three gatehouses that were once military checkpoints controlling access to Atomic Energy Commission production facilities.
John D. Metzger, Mohamed S. El-Genk,Alexander G. Parlos
Nuclear Science and Engineering | Volume 109 | Number 2 | October 1991 | Pages 171-187
Technical Paper | doi.org/10.13182/NSE91-A28516
Articles are hosted by Taylor and Francis Online.
To ensure that a space nuclear power system will operate safely and respond in a predictable and desired manner, the system’s controller design must account for changes in the system parameters over its lifetime. A model reference adaptive controller is applied to enable the actual space nuclear power system to follow a predictable and desired response of a reference model system, despite changes in the actual system’s operating parameters. Model reference adaptive control is well developed for linear systems and has been applied to simple, single-input, single-output (and the output’s derivative) systems. Model reference adaptive control is applied to a single-input, multiple-output nonlinear system but also shows the development for a multiple-input, multiple-output linear system. An algorithm is developed for linear systems to determine the constant gains in the model reference adaptive control algorithm and a method is developed that allows selective weighting of a desired state variable. Examples are presented to show that a model reference adaptive controller can ensure the load-following response of a nonlinear space nuclear power system and that the reference model can be complex enough to embody the physics of the plant. The results of the example cases show that a model reference adaptive controller can cause a selected nonlinear plant state variable to track the transient trajectory of the corresponding state variable of the reference model with local stability.