Control of the VVER-1000 core power using optimized T-S fuzzy controller based on nonlinear point kinetic model

It is important for nuclear power plants (NPPs) to have the capability to adjust their output to meet the requirements of the power system. This calls for the development of efficient control algorithms to preserve steady/ safe operating conditions. The current research proposes an optimized Takagi-Sugeno (T-S) fuzzy control algorithm to regulate the core power level of a VVER-1000 reactor. In the research, a straightforward method of tuning and optimizing T-S fuzzy controller is presented. The designed controller has a nonlinear mathematical structure of PI controller which has parameters that interpolate smoothly among a number of linear classical PI controllers. T-S fuzzy controller gains are optimized using sequential quadratic programming (SQP). The objective function is defined as a weighted sum of a performance index, the integrated time absolute error (ITAE), and the stabilization time based on Lyapunov synthesis. Simulations are conducted based on a nonlinear point kinetic model of VVER-1000 reactor to evaluate the proposed approach. The performance is investigated in load-tracking mode at different rates and in the presence of external disturbances. The results demonstrate the superiority of the optimized T-S fuzzy control strategy in terms of tracking accuracy and responses to disturbances compared to conventional control methods.