[en] This paper introduces an automatic control system incorporating a number of verification, validation, and command generation tasks with-in a fault-tolerant architecture. The integrated system utilizes recent methods of artificial intelligence such as neural networks and fuzzy logic control. Furthermore, advanced signal processing and nonlinear control methods are also included in the design. The primary goal is to create an on-line capability to validate signals, analyze plant performance, and verify the consistency of commands before control decisions are finalized. The application of this approach to the automated startup of the Experimental Breeder Reactor-II (EBR-II) is performed using a validated nonlinear model. The simulation results show that the advanced concepts have the potential to improve plant availability andsafety