[en] Under the influence of nuclear radiation, the reliability of steam generators (SGs) is an important factor in the efficiency and safety of nuclear power plant (NPP) reactors. Motion planning that remotely manipulates an SG mobile tube-inspection robot to inspect SG heat transfer tubes is the mainstream trend of NPP robot development. To achieve motion planning, conditional traversal is usually used for base position optimization, and then the A* algorithm is used for path planning. However, the proposed approach requires considerable processing time and has a single expansion during path planning and plan paths with many turns, which decreases the working speed of the robot. Therefore, to reduce the calculation time and improve the efficiency of motion planning, modifications such as the matrix method, improved parent node, turning cost, and improved expanded node were proposed in this study. We also present a comprehensive evaluation index to evaluate the performance of the improved algorithm. We validated the efficiency of the proposed method by planning on a tube sheet with square-type tube arrays and experimenting with Model SG

[en] In order to further improve the safety of nuclear power plants, based on the nonlinear system with stochastic noise, the strong tracking filter is used to evaluate the sensor fault bias of steam generator control system and reconstruct the sensors output to implement the fault tolerant control. The simulation results demonstrate that this method can evaluate the time-varying sensor fault bias effectively and has great fault tolerant ability, and the methodology employing the strong tracking filter for steam generator fault tolerant control design is effective. (authors)