An intelligent multi-step predictive control method of the Small Modular Reactor

Abstract

As Small Modular Reactors (SMRs) feature great complexity and uncertainty in response and are varying over time during long-term operation, it is of difficulty to design a well-performed controller that can deal with different working conditions. In this paper, an intelligent multi-step predictive scheme is created to support the development of autonomous control for SMRs. In this scheme, an adaptive prediction model is constructed using T-S fuzzy identification with training data generated by cases of reactor system model, and a real-time adaptive algorithm is utilized to update model parameters to improve accuracy of prediction. Particle swarm optimization (PSO) has also been carried out to search for the optimal decision. The simulation results manifest the effectiveness and the good performance of the proposed approach.