F. Wallam, A. Memon, Chee Pin Tan
2026.2.17NUCLEAR TECHNOLOGY
Abstract
Nuclear power plants generate clean and cheap energy in comparison with fossil fuel–based power plants. However, nuclear reactors belong to the class of systems that are complex and unstable in nature. Due to their high-order nonlinear dynamics and open-loop instability, the design of control schemes for such a class of energy-generating systems is an important engineering problem. The important features of the control scheme for nuclear reactors are good reference tracking and disturbance rejection capabilities. In addition to these features, it is also desired that the control system should possess a simplified and low-complexity design. Thus, in this paper, we consider the problem of designing a low-complexity model-free control scheme for robust tracking of a load-following pressurized water reactor (PWR). To solve this problem, we consider a funnel control technique; however, the basic funnel control algorithm requires a sufficient smoothness of the reference signal, and therefore, it may not be simply applied for the load-following operation of a PWR. To overcome this drawback, we propose a shifting-funnel function–based funnel control. The proposed funnel algorithm ensures the stability of the PWR in load-following mode by confining the error surface within the prespecified boundary even when a change in power demand is not sufficiently smooth. A detailed mathematical analysis of the closed-loop system is carried out to investigate the stability of the proposed scheme. For validating the performance of the closed-loop system, different simulation scenarios are considered and evaluated. The results of these simulation scenarios show that the proposed control scheme efficiently tracks the power demand while effectively rejecting disturbances.
Citation format
WALLAM, F.; MEMON, A.; TAN, Chee Pin. Shifting-funnel function based funnel control: A model-free control approach for load-following operation of pressurized water reactor. NUCLEAR TECHNOLOGY, 2026: 1–18.