Cognitive Control Method for Cost-Efficient Communication-Based Train Control Systems in Smart Grids

In Communication-based Train Control (CBTC) systems, the information uncertainties due to unreliable wireless networks leads to imperfect braking demands, which increases the energy consumption. Moreover, with the development of power grid technology, smart grid can be applied in CBTC systems to reduce the electricity cost. In this paper, we introduce a cognitive control method to improve performance of CBTC systems in smart grid environment. A cognitive control system is presented and the performance optimization problem in smart grid environment is formulated as Semi-Markov Decision Process (SMDP), where Medium Access Control (MAC)-layer parameters adaption and feedback gain adaption are applied to minimize both electricity cost and information uncertainty of CBTC systems. Simulation results show that the proposed cognitive control scheme can improve the cost-efficiency of CBTC systems.