Evolutionary Reinforcement Learning: A Hybrid Approach for Safety-informed Intelligent Fault-tolerant Flight Control

Recent research in bio-inspired artificial intelligence potentially provides solutions to the challenging problem of designing fault-tolerant and robust flight control systems. The current work proposes SERL, a novel Safety-informed Evolutionary Reinforcement Learning algorithm, which combines Deep Reinforcement Learning (DRL) and neuro...

Deep Reinforcement Learning for Aircraft Landing: A study on the use of Deep Reinforcement Learning techniques for automatic control of aircraft landing

Safe & Intelligent Control: Fault-tolerant Flight Control with Distributional and Hybrid Reinforcement Learning using DSAC and IDHP

The critical challenge for employing autonomous control systems in aircraft is ensuring robustness and safety. This study introduces an intelligent and fault-tolerant controller that merges two Reinforcement Learning (RL) algorithms in a hybrid approach: the Distributional Soft Actor-Critic (DSAC) and the Incremental Dual Heuristic Programming ...