Reinforcement Learning for Safe Robot Control using Control Lyapunov Barrier Functions

Reinforcement learning (RL) exhibits impressive performance when managing complicated control tasks for robots. However, its wide application to physical robots is limited by the absence of strong safety guarantees. To overcome this challenge, this paper explores the control Lyapunov barrier function (CLBF) to analyze the safety and reachability...

Effect of CO₂-based binary mixtures on the performance of radial-inflow turbines for the supercritical CO₂ cycles

Recently, the supercritical carbon dioxide (SCO₂) power cycle has become a hotspot in the field of energy-efficient utilization. The utilization of additives in the power cycle has been proven to be an effective way to improve the SCO₂ power cycle efficiency. As one of the core components of the system, the influence of...