A Takagi Sugeno based reactor power control of VVER-1000 using linear parameter varying identification of two-point kinetic model

Highlights: • An optimized fuzzy control with action based scaled linear output synthesis. • Representing complex nonlinear system with unique linear parameter varying models. • Effect of neutron diffusion, heat transfer and coupling coefficients for reactor model. • Weighted output framework of LPV subsystems with interpolation hypothesis. • Effective handling of disturbances due to load variations and accidental scenarios. This study aims to design Takagi Sugeno (TS) Fuzzy logic based power control for VVER-1000 PWR to achieve smooth and precise load following situations under various disturbances and model uncertainties. To achieve the purpose, a two-point kinetic model with consideration of neutron diffusion, thermal hydraulics and poison concentration is developed. Model identification for the equivalent linear parameter varying (LPV) system is performed using the fixed functional parameters and reproducing the corresponding LPV subsystems for each of those functional points in the form of SISO transfer function synthesis. Linear heft factors are introduced to compute the weighted output based on the triangular and trapezoidal membership functions of fuzzy logic. Linear interpolation is used to find the controlled power based on heft factors and operational specifications of the nuclear reactor over the entire power range. A TS fuzzy based controller with fixed gain and parameters is designed to efficiently control the reactor power under multiple transient conditions. The LPV subsystems are to be controlled with the fuzzy controller comprising two inputs with effective utilization of unsymmetrical, nonlinear and optimized membership functions and scaled output linear function of fuzzy variables. Stability analysis is performed using the Lyapunov like function and the condition is demonstrated for the two-point kinetic model of the reactor. The performance of the proposed framework is evaluated for load following scenarios with fast and slow ramp changes; along with accident handling with positive reactivity insertion tests. The proposed TS fuzzy power control model found preferably efficient in load tracking applications and disturbance rejection conditions.