This article investigates the velocity and input constrained tracking control problem of discrete-time high-speed train systems. A distributed cooperative tracking control algorithm is proposed for each train using the local information from its adjacent trains. Based on model transformation and the convex analysis approach, it is shown that all trains eventually cooperative run in a stable mode while tracking the desired speed. Finally, a simulation example is given to demonstrate the obtained theoretical results.

Human error can be regarded as a significant factor contributing to high-speed railway accidents. Cognitive Reliability and Error Analysis Method (CREAM) is well-known approach applied to determine Human Error Probability (HEP). However, shortcomings are still disclosed and weaken the applicability of such approach. These include the lack of sufficient failure data, lack of valid description of Common Performance Condition (CPC) and does not consider the CPCs weights. In addition, Basic CREAM does not provide a method to calculate the concrete HEP. In this paper, a modified CREAM is proposed to assess HEP of high-speed railway dispatchers in dispatching tasks. The core of the modified method is to use 2-tuple linguistic term sets to describe CPCs evaluation, combine weighted CPCs by Evidential Reasoning (ER) approach, and adopt Multi-Attribute Group Decision-Making (MAGDM) method to calculate HEP. To make CPCs weights more accurate, dynamically adjusting weights is adopted in this paper. The rationality and validity of the modified CREAM approach are verified by two axioms and compared other models. Finally this modified CREAM approach is applied to human reliability analysis of high-speed railway dispatchers.

This paper investigates the robust uncertain two-level cooperative set covering problem (RUTLCSCP). Given two types of facilities, which are called y-facility and z-facility. The problem is to decide which facilities of both types to be selected, in order to cover the demand nodes cooperatively with minimal cost. It combines the concepts of robust, probabilistic, and cooperative covering by introducting "$\Gamma$-robust two-level-cooperative $\alpha$-cover" constraints. Additionally, the constraint relaxed verison of the RUTLCSCP, which is also a linear approximation robust counterpart version of RUTLCSCP (RUTLCSCP-LA-RC), is developed by linear approximation of the constraints, and can be stated as a compact mixed-integer linear programming problem. We show that the solution for RUTLCSCP-LA-RC, $\varepsilon$-under-approximate solution, can also be the solution for RUTLCSCP on some conditions. Computational experiments show that the solutions in 333 instances (10125 instances in total) with 12 types which tinily violate the constraints of RUTLCSCP, can be an efficient under-approximate solutions, while the feasible solutions in other instances are proven to be optimal.