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 ...

Incremental Model Based Actor Critic Design for Optimal Adaptive Flight Control: Investigation and Implementation of Online Flight Control Methods

To solve the problem of optimal control for nonlinear system, Actor Critic Designs (ACD) can be utilized which use the concept of Reinforcement learning (RL) and function approximators such as Neural networks (NN). Traditional ACD methods require a model NN that needs to be trained offline. Recently, research focus has been shifted to model-free...