Flight Testing Reinforcement Learning based Online Adaptive Flight Control Laws on CS-25 Class Aircraft

Unforeseen failures during flight can lead to Loss of Control In-Flight, a significant cause of fatal aircraft accidents worldwide. Current offline synthesized flight control methods have limited capability to recover from failures, due to their limited adaptability. Incremental Approximate Dynamic Programming (iADP) control is a model-agnostic...

Reinforcement Learning based Online Adaptive Flight Control for the Cessna Citation II(PH-LAB) Aircraft

OnlineAdaptive Flight Control is interesting in the context of growing complexity of aircraft systems and their adaptability requirements to ensure safety. An Incremental Approximate Dynamic Programming (iADP) controller combines reinforcement learning methods, optimal control and online identified incremental model to achieve optimal adaptive...

Flight testing of incremental backstepping based control laws with angular accelerometer feedback

This paper discusses the design, implementation and flight testing of an incremental Backstepping (IBS) based manual flight control law with angular accelerometer (AA) feedback. The main advantages of incremental control laws are that they only require a partial model of the system and are of low complexity. Incremental control laws for...

Design and flight testing of incremental nonlinear dynamic inversion based control laws for a passenger aircraft

This paper describes the design, implementation and flight testing of flight control laws based on Incremental Nonlinear Dynamic Inversion (INDI). The method compares com- manded and measured accelerations to compute increments on the current control de ec- tions. This results in highly robust control solutions with respect to model...